==2277988== Memcheck, a memory error detector ==2277988== Copyright (C) 2002-2024, and GNU GPL'd, by Julian Seward et al. ==2277988== Using Valgrind-3.24.0 and LibVEX; rerun with -h for copyright info ==2277988== Command: /data/blackswan/ripley/R/R-devel-vg/bin/exec/R --vanilla ==2277988== R Under development (unstable) (2026-02-16 r89423) -- "Unsuffered Consequences" Copyright (C) 2026 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > pkgname <- "event" > source(file.path(R.home("share"), "R", "examples-header.R")) > options(warn = 1) > library('event') Loading required package: rmutil Attaching package: ‘rmutil’ The following object is masked from ‘package:stats’: nobs The following objects are masked from ‘package:base’: as.data.frame, units > > base::assign(".oldSearch", base::search(), pos = 'CheckExEnv') > base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv') > cleanEx() > nameEx("autointensity") > ### * autointensity > > flush(stderr()); flush(stdout()) > > ### Name: autointensity > ### Title: Plot Autointensity Function of a Point Process > ### Aliases: autointensity > ### Keywords: hplot > > ### ** Examples > > times <- rgamma(100,2,scale=4) > autointensity(times, window=3) > > > > cleanEx() > nameEx("bp") > ### * bp > > flush(stderr()); flush(stdout()) > > ### Name: bp > ### Title: Create a Vector of Cumulative Numbers of Previous Events for a > ### Point Process (Birth Processes) > ### Aliases: bp > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > i <- c(1,1,2,2) > birth <- bp(y, i) > birth [1] 0 0 0 0 0 1 1 1 0 0 1 1 1 1 > > > > cleanEx() > nameEx("coxre") > ### * coxre > > flush(stderr()); flush(stdout()) > > ### Name: coxre > ### Title: Cox Proportional Hazards Model with Random Effect > ### Aliases: coxre print.llrf > ### Keywords: models > > ### ** Examples > > # 11 individuals, each with 5 responses > y <- matrix(c(51,36,50,35,42, + 27,20,26,17,27, + 37,22,41,37,30, + 42,36,32,34,27, + 27,18,33,14,29, + 43,32,43,35,40, + 41,22,36,25,38, + 38,21,31,20,16, + 36,23,27,25,28, + 26,31,31,32,36, + 29,20,25,26,25),ncol=5,byrow=TRUE) > # Different intensity functions > coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, + est=0.7, stratified=TRUE) Stratified Cox proportional hazards model with gamma frailty Call: coxre(response = y, censor = matrix(rep(1, 55), ncol = 5), nest = 1:11, est = 0.7, stratified = TRUE) -Log likelihood 126.3376 Degrees of freedom 6 AIC 175.3376 Iterations 2 gamma = 0.7123921 correlation = 0.3831395 Regression coefficients: (Intercept) -2.637733 Fixed effects: 1 2 3 4 5 6 0.04508930 2.54649734 0.99559248 0.39620871 3.78376536 4.36021345 7 8 9 10 11 12 2.85155056 15.19457491 32.42712131 11.88733143 0.06512899 1.36010945 13 14 15 16 17 18 2.33548856 6.33463000 4.35346859 0.93683082 15.19457491 10.99143247 19 20 21 22 23 24 0.04689287 1.40576796 1.83167247 1.11191216 3.70907366 4.26194753 25 26 27 28 29 30 2.85238383 3.04049262 16.21356065 13.58552163 0.08373727 0.45336982 31 32 33 34 35 36 0.58497068 0.87455011 3.22557551 0.98988924 4.96261197 30.40492624 37 38 39 40 41 42 14.31006962 0.07327011 0.15003721 1.66971710 2.50926261 3.30851804 43 44 45 46 47 5.42073206 1.11455511 6.10344954 16.21356065 47.54932572 Random effects: 1 2 3 4 5 6 7 8 0.1437091 2.3526328 0.4868738 0.4860624 1.6660830 0.2808677 0.7155620 1.5899889 9 10 11 1.3594625 0.9497731 2.0098322 > # Proportional intensity functions for the five responses > coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, + est=0.7, stratified=FALSE) Cox proportional hazards model with gamma frailty Call: coxre(response = y, censor = matrix(rep(1, 55), ncol = 5), nest = 1:11, est = 0.7, stratified = FALSE) -Log likelihood 163.4521 Degrees of freedom 21 AIC 197.4521 Iterations 2 gamma = 0.8907636 correlation = 0.4584099 Regression coefficients: (Intercept) resp2 resp3 resp4 resp5 -3.6281678 2.3562336 0.5615743 1.9280003 1.0898560 Fixed effects: 1 2 3 4 5 6 9.386873e-03 6.911260e-02 1.409360e-01 1.504643e-01 2.469569e-01 2.228434e-01 7 8 9 10 11 12 4.998805e-01 2.715448e-01 6.134907e-01 1.156066e+00 2.403159e+00 6.024137e-01 13 14 15 16 17 18 1.299450e+00 7.583284e-01 2.341333e+00 3.007212e+00 1.247655e+00 1.419677e+00 19 20 21 22 23 24 3.146013e+00 8.783661e+00 6.528740e+00 9.615225e+00 4.678915e+00 2.270592e+01 25 26 27 28 4.201789e+01 7.372914e+01 1.491668e+01 2.860966e+02 Random effects: 1 2 3 4 5 6 7 8 0.1251022 2.5491149 0.4698635 0.3752438 2.1178225 0.2330259 0.6809870 1.7961565 9 10 11 1.5594363 0.6223883 2.1557178 > # Identical intensity functions > coxre(response=as.vector(t(y)), censor=rep(1,55), + nest=rep(1:11,rep(5,11)), est=0.7) Stratified Cox proportional hazards model with gamma frailty Call: coxre(response = as.vector(t(y)), censor = rep(1, 55), nest = rep(1:11, rep(5, 11)), est = 0.7) -Log likelihood 176.0124 Degrees of freedom 25 AIC 206.0124 Iterations 3 gamma = 0.4231517 correlation = 0.2419091 Regression coefficients: (Intercept) -2.739641 Fixed effects: 1 2 3 4 5 6 0.01978612 0.14234482 0.29121447 0.30137738 0.46574270 0.34311332 7 8 9 10 11 12 0.70527154 0.36418546 0.75025621 1.29501069 2.46833092 0.63532232 13 14 15 16 17 18 1.33877190 0.77833468 2.41821379 2.89860461 1.10678801 1.24057362 19 20 21 22 23 24 2.61934616 6.93323077 4.23314623 5.20774599 1.92591174 8.54216858 25 26 27 28 13.86970985 23.59335600 4.22651740 59.17124359 Random effects: 1 2 3 4 5 6 7 8 0.2590148 1.8040818 0.6844730 0.6580569 1.5160417 0.3926501 0.7078798 1.2218770 9 10 11 1.2448293 0.9851468 1.7396023 > > > > cleanEx() > nameEx("cprocess") > ### * cprocess > > flush(stderr()); flush(stdout()) > > ### Name: cprocess > ### Title: Plot Counting Process Data > ### Aliases: cprocess > ### Keywords: hplot > > ### ** Examples > > times <- rgamma(20,2,scale=4) > cprocess(times) > > > > cleanEx() > nameEx("ehr") > ### * ehr > > flush(stderr()); flush(stdout()) > > ### Name: ehr > ### Title: Regression Models for Event History Intensity Functions > ### Aliases: ehr print.intensity deviance.intensity vdm > ### Keywords: models > > ### ** Examples > > y <- c(5,3,2,4) > # event indicator > py <- pp(y) > # time since previous event > ptime <- tpast(y) > # individual ID > i <- c(1,1,2,2) > id <- ident(y, i) > # times and corresponding covariate values > tx <- c(2,3,1,2,2,2,2) > x <- c(1,2,2,1,2,2,1) > zcov <- tvcov(y, x, tx) > # Poisson process > ehr(py, plambda=1) Call: ehr(py, plambda = 1) Log intensity function: p[1] * rep(1, n) -Log likelihood 9.011052 AIC 10.01105 Iterations 8 Coefficients: estimate se p[1] -1.253 0.4999 > # Weibull process > lambda1 <- function(p) p[1]+p[2]*log(ptime) > ehr(py, lambda=lambda1, plambda=c(1,1)) Call: ehr(py, lambda = lambda1, plambda = c(1, 1)) Log intensity function: p[1] + p[2] * log(ptime) -Log likelihood 7.456457 AIC 9.456457 Iterations 18 Coefficients: estimate se p[1] -3.191 1.611 p[2] 1.944 1.279 Correlations: 1 2 1 1.0000 -0.9506 2 -0.9506 1.0000 > # or > ehr(py, lambda=~log(ptime), plambda=c(1,1)) Call: ehr(py, lambda = ~log(ptime), plambda = c(1, 1)) Log intensity function: ~log(ptime) -Log likelihood 7.456457 AIC 9.456457 Iterations 18 Coefficients: estimate se (Intercept) -3.191 1.611 log(ptime) 1.944 1.279 Correlations: 1 2 1 1.0000 -0.9506 2 -0.9506 1.0000 > # or > ehr(py, lambda=~b0+b1*log(ptime), plambda=list(b0=1,b1=1)) Call: ehr(py, lambda = ~b0 + b1 * log(ptime), plambda = list(b0 = 1, b1 = 1)) Log intensity function: ~b0 + b1 * log(ptime) -Log likelihood 7.456457 AIC 9.456457 Iterations 18 Coefficients: estimate se b0 -3.191 1.611 b1 1.944 1.279 Correlations: 1 2 1 1.0000 -0.9506 2 -0.9506 1.0000 > # Poisson process with time-varying covariate > lambda2 <- function(p) p[1]+p[2]*zcov > ehr(py, lambda=lambda2, plambda=c(1,1)) Call: ehr(py, lambda = lambda2, plambda = c(1, 1)) Log intensity function: p[1] + p[2] * zcov -Log likelihood 8.969813 AIC 10.96981 Iterations 20 Coefficients: estimate se p[1] -0.8110 1.5803 p[2] -0.2876 0.9993 Correlations: 1 2 1 1.0000 -0.9487 2 -0.9487 1.0000 > # or > ehr(py, lambda=~zcov, plambda=c(1,1)) Call: ehr(py, lambda = ~zcov, plambda = c(1, 1)) Log intensity function: ~zcov -Log likelihood 8.969813 AIC 10.96981 Iterations 20 Coefficients: estimate se (Intercept) -0.8110 1.5803 zcov -0.2876 0.9993 Correlations: 1 2 1 1.0000 -0.9487 2 -0.9487 1.0000 > # or > ehr(py, lambda=~c0+c1*zcov, plambda=list(c0=1,c1=1)) Call: ehr(py, lambda = ~c0 + c1 * zcov, plambda = list(c0 = 1, c1 = 1)) Log intensity function: ~c0 + c1 * zcov -Log likelihood 8.969813 AIC 10.96981 Iterations 20 Coefficients: estimate se c0 -0.8110 1.5803 c1 -0.2876 0.9993 Correlations: 1 2 1 1.0000 -0.9487 2 -0.9487 1.0000 > # Weibull process with time-varying covariate > lambda3 <- function(p) p[1]+p[2]*log(ptime)+p[3]*zcov > ehr(py, lambda=lambda3, plambda=c(1,1,1)) Call: ehr(py, lambda = lambda3, plambda = c(1, 1, 1)) Log intensity function: p[1] + p[2] * log(ptime) + p[3] * zcov -Log likelihood 7.395952 AIC 10.39595 Iterations 27 Coefficients: estimate se p[1] -2.7634 2.042 p[2] 2.0490 1.385 p[3] -0.3587 1.029 Correlations: 1 2 3 1 1.0000 -0.6332 -0.5633 2 -0.6332 1.0000 -0.2369 3 -0.5633 -0.2369 1.0000 > # or > ehr(py, lambda=~log(ptime)+zcov, plambda=c(1,1,1)) Call: ehr(py, lambda = ~log(ptime) + zcov, plambda = c(1, 1, 1)) Log intensity function: ~log(ptime) + zcov -Log likelihood 7.395952 AIC 10.39595 Iterations 27 Coefficients: estimate se (Intercept) -2.7634 2.042 log(ptime) 2.0490 1.385 zcov -0.3587 1.029 Correlations: 1 2 3 1 1.0000 -0.6332 -0.5633 2 -0.6332 1.0000 -0.2369 3 -0.5633 -0.2369 1.0000 > # or > ehr(py, lambda=~c0+b1*log(ptime)+c1*zcov, plambda=list(c0=1,c1=1,b1=1)) Call: ehr(py, lambda = ~c0 + b1 * log(ptime) + c1 * zcov, plambda = list(c0 = 1, c1 = 1, b1 = 1)) Log intensity function: ~c0 + b1 * log(ptime) + c1 * zcov -Log likelihood 7.395952 AIC 10.39595 Iterations 27 Coefficients: estimate se c0 -2.7634 2.042 b1 2.0490 1.385 c1 -0.3587 1.029 Correlations: 1 2 3 1 1.0000 -0.6332 -0.5633 2 -0.6332 1.0000 -0.2369 3 -0.5633 -0.2369 1.0000 > # gamma process with time-varying covariate > lambda4 <- function(p) hgamma(ptime, p[1], exp(p[2]+p[3]*zcov)) > ehr(py, lambda=lambda4, plambda=c(1,1,1)) Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in sqrt(diag(cov)) : NaNs produced Call: ehr(py, lambda = lambda4, plambda = c(1, 1, 1)) Log intensity function: hgamma(ptime, p[1], exp(p[2] + p[3] * zcov)) -Log likelihood 18.26965 AIC 21.26965 Iterations 11 Coefficients: estimate se p[1] 4.849e-04 0.02778 p[2] -7.785e+00 NaN p[3] -1.467e+01 NaN Correlations: 1 2 3 1 1 NaN NaN 2 NaN NaN NaN 3 NaN NaN NaN > # or > ehr(py, lambda=~hgamma(ptime, b1, exp(c0+c1*zcov)), + plambda=list(c0=1,c1=1,b1=1)) Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in sqrt(diag(cov)) : NaNs produced Call: ehr(py, lambda = ~hgamma(ptime, b1, exp(c0 + c1 * zcov)), plambda = list(c0 = 1, c1 = 1, b1 = 1)) Log intensity function: ~hgamma(ptime, b1, exp(c0 + c1 * zcov)) -Log likelihood 18.26965 AIC 21.26965 Iterations 11 Coefficients: estimate se b1 4.849e-04 0.02778 c0 -7.785e+00 NaN c1 -1.467e+01 NaN Correlations: 1 2 3 1 1 NaN NaN 2 NaN NaN NaN 3 NaN NaN NaN > # or > lambda5 <- function(p, linear) hgamma(ptime, p[1], exp(linear)) > ehr(py, lambda=lambda5, linear=~zcov, plambda=c(1,1,1)) Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in dgamma(y, shape, scale = scale, log = TRUE) : NaNs produced Warning in pgamma(y, shape, scale = scale, lower.tail = FALSE, log.p = TRUE) : NaNs produced Warning in nlm(fn, p = plambda, hessian = TRUE, print.level = print.level, : NA/NaN replaced by maximum positive value Warning in sqrt(diag(cov)) : NaNs produced Call: ehr(py, lambda = lambda5, linear = ~zcov, plambda = c(1, 1, 1)) Log intensity function: hgamma(ptime, p[1], exp(linear)) -Log likelihood 18.26965 AIC 21.26965 Iterations 11 Coefficients: estimate se p[1] 4.849e-04 0.02778 (Intercept) -7.785e+00 NaN zcov -1.467e+01 NaN Correlations: 1 2 3 1 1 NaN NaN 2 NaN NaN NaN 3 NaN NaN NaN > > > > cleanEx() > nameEx("hboxcox") > ### * hboxcox > > flush(stderr()); flush(stdout()) > > ### Name: hboxcox > ### Title: Log Hazard Function for a Box-Cox Process > ### Aliases: hboxcox > ### Keywords: distribution > > ### ** Examples > > hboxcox(2, 5, 5, 2) [1] -1.836358 > > > > cleanEx() > nameEx("hburr") > ### * hburr > > flush(stderr()); flush(stdout()) > > ### Name: hburr > ### Title: Log Hazard Function for a Burr Process > ### Aliases: hburr > ### Keywords: distribution > > ### ** Examples > > hburr(2, 5, 1, 2) [1] -1.252763 > > > > cleanEx() > nameEx("hcauchy") > ### * hcauchy > > flush(stderr()); flush(stdout()) > > ### Name: hcauchy > ### Title: Log Hazard Function for a Cauchy Process > ### Aliases: hcauchy > ### Keywords: distribution > > ### ** Examples > > hcauchy(1:10, 3, 2) [1] -2.243342 -1.626513 -1.144730 -1.018079 -1.144730 -1.340778 -1.533955 [8] -1.707896 -1.861754 -1.998088 > > > > cleanEx() > nameEx("hexp") > ### * hexp > > flush(stderr()); flush(stdout()) > > ### Name: hexp > ### Title: Log Hazard Function for a Poisson Process > ### Aliases: hexp > ### Keywords: distribution > > ### ** Examples > > hexp(1:10, 3) [1] 1.098612 1.098612 1.098612 1.098612 1.098612 1.098612 1.098612 1.098612 [9] 1.098612 1.098612 > > > > cleanEx() > nameEx("hgamma") > ### * hgamma > > flush(stderr()); flush(stdout()) > > ### Name: hgamma > ### Title: Log Hazard Function for a Gamma Process > ### Aliases: hgamma > ### Keywords: distribution > > ### ** Examples > > hgamma(1:10, 3, 2) [1] -0.2231436 0.2076394 0.3646431 0.4453110 0.4942963 0.5271620 [7] 0.5507268 0.5684437 0.5822465 0.5933018 > > > > cleanEx() > nameEx("hgextval") > ### * hgextval > > flush(stderr()); flush(stdout()) > > ### Name: hgextval > ### Title: Log Hazard Function for an Extreme Value Process > ### Aliases: hgextval > ### Keywords: distribution > > ### ** Examples > > hgextval(1, 2, 1, 2) [1] 1.693147 > > > > cleanEx() > nameEx("hggamma") > ### * hggamma > > flush(stderr()); flush(stdout()) > > ### Name: hggamma > ### Title: Log Hazard Function for a Generalized Gamma Process > ### Aliases: hggamma > ### Keywords: distribution > > ### ** Examples > > hggamma(2, 5, 4, 2) [1] 1.109277 > > > > cleanEx() > nameEx("hglogis") > ### * hglogis > > flush(stderr()); flush(stdout()) > > ### Name: hglogis > ### Title: Log Hazard Function for a Generalized Logistic Process > ### Aliases: hglogis > ### Keywords: distribution > > ### ** Examples > > hglogis(5, 5, 1, 2) [1] -1.098612 > > > > cleanEx() > nameEx("hgweibull") > ### * hgweibull > > flush(stderr()); flush(stdout()) > > ### Name: hgweibull > ### Title: Log Hazard Function for a Generalized Weibull Process > ### Aliases: hgweibull > ### Keywords: distribution > > ### ** Examples > > hgweibull(5, 1, 3, 2) [1] -1.208747 > > > > cleanEx() > nameEx("hhjorth") > ### * hhjorth > > flush(stderr()); flush(stdout()) > > ### Name: hhjorth > ### Title: Log Hazard Function for a Hjorth Process > ### Aliases: hhjorth > ### Keywords: distribution > > ### ** Examples > > hhjorth(5, 5, 5, 2) [1] -1.284016 > > > > cleanEx() > nameEx("hinvgauss") > ### * hinvgauss > > flush(stderr()); flush(stdout()) > > ### Name: hinvgauss > ### Title: Log Hazard Function for a Inverse Gauss Process > ### Aliases: hinvgauss > ### Keywords: distribution > > ### ** Examples > > hinvgauss(5, 5, 1) [1] -1.833394 > > > > cleanEx() > nameEx("hlaplace") > ### * hlaplace > > flush(stderr()); flush(stdout()) > > ### Name: hlaplace > ### Title: Log Hazard Function for a Laplace Process > ### Aliases: hlaplace > ### Keywords: distribution > > ### ** Examples > > hlaplace(5, 2, 1) [1] 1.776357e-15 > > > > cleanEx() > nameEx("hlnorm") > ### * hlnorm > > flush(stderr()); flush(stdout()) > > ### Name: hlnorm > ### Title: Log Hazard Function for a Log Normal Process > ### Aliases: hlnorm > ### Keywords: distribution > > ### ** Examples > > hlnorm(1:10, 3, 2) [1] -2.667942 -2.837620 -2.975217 -3.088321 -3.184259 -3.267660 -3.341521 [8] -3.407877 -3.468169 -3.523456 > > > > cleanEx() > nameEx("hlogis") > ### * hlogis > > flush(stderr()); flush(stdout()) > > ### Name: hlogis > ### Title: Log Hazard Function for a Logistic Process > ### Aliases: hlogis > ### Keywords: distribution > > ### ** Examples > > hlogis(1:10, 3, 2) [1] -2.0064089 -1.6672242 -1.3862944 -1.1672242 -1.0064089 -0.8945605 [7] -0.8200752 -0.7720369 -0.7417345 -0.7228976 > > > > cleanEx() > nameEx("hnorm") > ### * hnorm > > flush(stderr()); flush(stdout()) > > ### Name: hnorm > ### Title: Log Hazard Function for a Normal Process > ### Aliases: hnorm > ### Keywords: distribution > > ### ** Examples > > hnorm(1:10, 3, 2) [1] -1.93933193 -1.36813930 -0.91893853 -0.56117395 -0.27106407 -0.03114131 [7] 0.17109862 0.34456256 0.49564051 0.62897959 > > > > cleanEx() > nameEx("hpareto") > ### * hpareto > > flush(stderr()); flush(stdout()) > > ### Name: hpareto > ### Title: Log Hazard Function for a Pareto Process > ### Aliases: hpareto > ### Keywords: distribution > > ### ** Examples > > hpareto(5, 2, 2) [1] 0.3333333 > > > > cleanEx() > nameEx("hskewlaplace") > ### * hskewlaplace > > flush(stderr()); flush(stdout()) > > ### Name: hskewlaplace > ### Title: Log Hazard Function for a Skew Laplace Process > ### Aliases: hskewlaplace > ### Keywords: distribution > > ### ** Examples > > hskewlaplace(5, 2, 1, 0.5) [1] -0.6931472 > > > > cleanEx() > nameEx("hstudent") > ### * hstudent > > flush(stderr()); flush(stdout()) > > ### Name: hstudent > ### Title: Log Hazard Function for a Student t Process > ### Aliases: hstudent > ### Keywords: distribution > > ### ** Examples > > hstudent(1:10, 3, 2, 5) [1] -0.3719502 -0.1879525 0.1207822 0.5697309 1.1335358 1.7611760 [7] 2.4041582 3.0305185 3.6240373 4.1787313 > > > > cleanEx() > nameEx("hweibull") > ### * hweibull > > flush(stderr()); flush(stdout()) > > ### Name: hweibull > ### Title: Log Hazard Function for a Weibull Process > ### Aliases: hweibull > ### Keywords: distribution > > ### ** Examples > > hweibull(1:10, 1.5, 2) [1] -0.63425566 -0.28768207 -0.08494952 0.05889152 0.17046329 0.26162407 [7] 0.33869941 0.40546511 0.46435663 0.51703688 > > > > cleanEx() > nameEx("ident") > ### * ident > > flush(stderr()); flush(stdout()) > > ### Name: ident > ### Title: Create an Individual Identification Vector for a Point Process > ### Aliases: ident > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > i <- c(1,1,2,2) > id <- ident(y, i) > id [1] 1 1 1 1 1 1 1 1 2 2 2 2 2 2 > > > > cleanEx() > nameEx("kalsurv") > ### * kalsurv > > flush(stderr()); flush(stdout()) > > ### Name: kalsurv > ### Title: Repeated Events Models with Frailty or Serial Dependence > ### Aliases: kalsurv deviance.kalsurv fitted.kalsurv print.kalsurv > ### residuals.kalsurv > ### Keywords: models > > ### ** Examples > > treat <- c(0,0,1,1) > tr <- tcctomat(treat) > cens <- matrix(rbinom(20,1,0.9),ncol=5) > times <- # matrix(rweibull(20,2,1+3*rep(treat,5)),ncol=5) + matrix(c(1.36,0.18,0.84,0.65,1.44,1.79,1.04,0.43,1.35,1.63,2.15,1.15, + 1.21,5.46,1.58,3.44,4.40,2.75,4.78,2.44),ncol=5,byrow=TRUE) > times <- restovec(times, censor=cens) > reps <- rmna(times, ccov=tr) > # exponential intensity model with independence > kalsurv(times, pinitial=0.5, preg=1, dep="independence", + intensity="exponential") Warning in sqrt(diag(cov)) : NaNs produced Call: kalsurv(times, pinitial = 0.5, preg = 1, dep = "independence", intensity = "exponential") Number of subjects 4 Number of observations 20 Pareto distribution with renewal process exponential intensity with independence -Log likelihood 31.57605 Degrees of freedom 18 AIC 33.57605 Iterations 24 Location parameters estimate se (Intercept) 0.8574 0.2479 Nonlinear parameters estimate se parameter initial -17.33 NaN 2.965e-08 Correlation matrix 1 2 1 1 NaN 2 NaN NaN > # Weibull intensity model with independence > kalsurv(times, pinitial=0.5, preg=1, pshape=1, dep="independence", + intensity="Weibull") Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, preg = 1, pshape = 1, dep = "independence", intensity = "Weibull") Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with independence -Log likelihood 30.12091 Degrees of freedom 17 AIC 33.12091 Iterations 27 Location parameters estimate se (Intercept) 0.903 0.1746 Nonlinear parameters estimate se parameter initial -9.7992 42.1710 0.0000555 shape 0.3488 0.1873 1.4173045 Correlation matrix 1 2 3 1 1.000000 -0.006568 0.197519 2 -0.006568 1.000000 0.001662 3 0.197519 0.001662 1.000000 > # same model with serial update > kalsurv(times, pinitial=0.5, pdep=0.1, preg=1, pshape=1, dep="serial", + intensity="Weibull") Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : NA/NaN replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, pdep = 0.1, preg = 1, pshape = 1, dep = "serial", intensity = "Weibull") Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with Markov update -Log likelihood 28.87284 Degrees of freedom 16 AIC 32.87284 Iterations 23 Location parameters estimate se (Intercept) 0.5494 0.3711 Nonlinear parameters estimate se parameter initial 0.12407 0.9028 1.1321 depend 0.01405 1.5221 0.5035 shape 0.71270 0.2915 2.0395 Correlation matrix 1 2 3 4 1 1.0000 -0.5567 0.7326 -0.5917 2 -0.5567 1.0000 -0.4768 0.7024 3 0.7326 -0.4768 1.0000 -0.5441 4 -0.5917 0.7024 -0.5441 1.0000 > # try power variance family instead of gamma distribution for mixture > kalsurv(times, pinitial=0.5, pdep=0.1, preg=1, pshape=1, dep="serial", + intensity="Weibull", pfamily=0.1) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : NA/NaN replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, pdep = 0.1, preg = 1, pshape = 1, dep = "serial", intensity = "Weibull", pfamily = 0.1) Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with Markov update -Log likelihood 28.59129 Degrees of freedom 15 AIC 33.59129 Iterations 31 Location parameters estimate se (Intercept) 0.3418 0.6076 Nonlinear parameters estimate se parameter initial 1.0004 1.2263 2.7193 depend -0.8172 1.7014 0.3064 family 0.2893 0.3150 0.2893 shape 0.7839 0.3128 2.1900 Correlation matrix 1 2 3 4 5 1 1.0000 -0.8399 0.8568 -0.3824 -0.5990 2 -0.8399 1.0000 -0.7173 0.5989 0.5497 3 0.8568 -0.7173 1.0000 -0.4385 -0.5570 4 -0.3824 0.5989 -0.4385 1.0000 -0.1135 5 -0.5990 0.5497 -0.5570 -0.1135 1.0000 > # treatment effect with log link > kalsurv(times, pinitial=0.5, preg=c(1,0), pshape=1, intensity="Weibull", + ccov=treat) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Warning in sqrt(diag(cov)) : NaNs produced Call: kalsurv(times, pinitial = 0.5, preg = c(1, 0), pshape = 1, intensity = "Weibull", ccov = treat) Warning: no convergence - error 3 Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with independence -Log likelihood 23.39741 Degrees of freedom 16 AIC 27.39741 Iterations 28 Location parameters estimate se (Intercept) 0.2315 0.1541 treat 1.0743 0.2225 Nonlinear parameters estimate se parameter initial -13.1210 NaN 2.003e-06 shape 0.7818 0.2002 2.185e+00 Correlation matrix 1 2 3 4 1 1.0000 -0.68101 NaN 0.13977 2 -0.6810 1.00000 NaN -0.01106 3 NaN NaN NaN NaN 4 0.1398 -0.01106 NaN 1.00000 > # or equivalently > kalsurv(times, mu=~exp(a+b*treat), pinitial=0.1, preg=c(1,0), pshape=1, + intensity="Weibull", envir=reps) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Call: kalsurv(times, mu = ~exp(a + b * treat), pinitial = 0.1, preg = c(1, 0), pshape = 1, intensity = "Weibull", envir = reps) Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with independence -Log likelihood 23.39741 Degrees of freedom 16 AIC 27.39741 Iterations 28 Location parameters ~exp(a + b * treat) estimate se a 0.2315 0.1541 b 1.0743 0.2225 Nonlinear parameters estimate se parameter initial -12.7263 10.1110 2.972e-06 shape 0.7818 0.2003 2.185e+00 Correlation matrix 1 2 3 4 1 1.00000 -0.680566 -0.013311 0.139220 2 -0.68057 1.000000 0.011815 -0.009871 3 -0.01331 0.011815 1.000000 0.005937 4 0.13922 -0.009871 0.005937 1.000000 > # with identity link instead > kalsurv(times, mu=~treat, pinitial=0.5, preg=c(1,0), pshape=1, + intensity="Weibull") Warning in sqrt(diag(cov)) : NaNs produced Call: kalsurv(times, mu = ~treat, pinitial = 0.5, preg = c(1, 0), pshape = 1, intensity = "Weibull") Warning: no convergence - error 3 Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with independence -Log likelihood 23.39728 Degrees of freedom 16 AIC 27.39728 Iterations 34 Location parameters ~treat estimate se (Intercept) 1.261 NaN treat 2.431 0.1348 Nonlinear parameters estimate se parameter initial -21.9873 0.01904 2.825e-10 shape 0.7821 0.04838 2.186e+00 Correlation matrix 1 2 3 4 1 NaN NaN NaN NaN 2 NaN 1.0000 0.1039 -0.8968 3 NaN 0.1039 1.0000 0.1483 4 NaN -0.8968 0.1483 1.0000 > # or equivalently > kalsurv(times, mu=~a+b*treat, pinitial=0.5, preg=c(1,0), pshape=1, + intensity="Weibull", envir=reps) Warning in sqrt(diag(cov)) : NaNs produced Call: kalsurv(times, mu = ~a + b * treat, pinitial = 0.5, preg = c(1, 0), pshape = 1, intensity = "Weibull", envir = reps) Warning: no convergence - error 3 Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with independence -Log likelihood 23.39728 Degrees of freedom 16 AIC 27.39728 Iterations 34 Location parameters ~a + b * treat estimate se a 1.261 NaN b 2.431 0.1348 Nonlinear parameters estimate se parameter initial -21.9873 0.01904 2.825e-10 shape 0.7821 0.04838 2.186e+00 Correlation matrix 1 2 3 4 1 NaN NaN NaN NaN 2 NaN 1.0000 0.1039 -0.8968 3 NaN 0.1039 1.0000 0.1483 4 NaN -0.8968 0.1483 1.0000 > # add the birth model > kalsurv(times, pinitial=0.5, preg=c(1,0), pshape=1, + intensity="Weibull", ccov=treat, pbirth=0) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, preg = c(1, 0), pshape = 1, intensity = "Weibull", ccov = treat, pbirth = 0) Number of subjects 4 Number of observations 20 Pareto distribution with birth process Weibull intensity with independence -Log likelihood 21.12467 Degrees of freedom 15 AIC 26.12467 Iterations 35 Location parameters estimate se (Intercept) 0.26519 NA treat 1.08104 NA birth -0.03824 NA Nonlinear parameters estimate se parameter initial -31.2199 NA 2.763e-14 shape 0.7809 NA 2.183e+00 Correlation matrix 1 2 3 4 5 1 NA NA NA NA NA 2 NA NA NA NA NA 3 NA NA NA NA NA 4 NA NA NA NA NA 5 NA NA NA NA NA > # try frailty dependence > kalsurv(times, pinitial=0.5, preg=c(1,0), pshape=1, dep="frailty", + intensity="Weibull", ccov=treat) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, preg = c(1, 0), pshape = 1, dep = "frailty", intensity = "Weibull", ccov = treat) Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with frailty dependence and no weight -Log likelihood 23.18297 Degrees of freedom 16 AIC 27.18297 Iterations 18 Location parameters estimate se (Intercept) 0.2045 0.2181 treat 1.0885 0.3089 Nonlinear parameters estimate se parameter initial -1.5092 2.1654 0.2211 shape 0.7948 0.1993 2.2139 Correlation = 0.1306908 Correlation matrix 1 2 3 4 1 1.0000 -0.69256 -0.13581 0.08150 2 -0.6926 1.00000 0.04932 0.01720 3 -0.1358 0.04932 1.00000 0.07264 4 0.0815 0.01720 0.07264 1.00000 > # add autoregression > kalsurv(times, pinitial=0.5, preg=c(1,0), pshape=1, dep="frailty", + pdep=0.1, intensity="Weibull", ccov=treat) Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : Inf replaced by maximum positive value Warning in nlm(surv, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : NA/NaN replaced by maximum positive value Call: kalsurv(times, pinitial = 0.5, preg = c(1, 0), pshape = 1, dep = "frailty", pdep = 0.1, intensity = "Weibull", ccov = treat) Number of subjects 4 Number of observations 20 Pareto distribution with renewal process Weibull intensity with frailty dependence no weight and AR -Log likelihood 17.70568 Degrees of freedom 15 AIC 22.70568 Iterations 23 Location parameters estimate se (Intercept) 1.4355 0.1688 treat 0.3753 0.3616 Nonlinear parameters estimate se parameter initial 1.193 1.4625 3.2964 AR -1.255 0.2805 0.2852 shape 1.177 0.2160 3.2438 Correlation = 0.879416 Correlation matrix 1 2 3 4 5 1 1.00000 -0.4790 -0.04023 -0.1780 -0.06525 2 -0.47899 1.0000 0.62037 -0.3660 0.30879 3 -0.04023 0.6204 1.00000 -0.6982 0.45427 4 -0.17797 -0.3660 -0.69824 1.0000 -0.13631 5 -0.06525 0.3088 0.45427 -0.1363 1.00000 > # switch to gamma intensity model > kalsurv(times, pinitial=0.5, preg=c(1,0), pshape=1, intensity="gamma", + ccov=treat) Call: kalsurv(times, pinitial = 0.5, preg = c(1, 0), pshape = 1, intensity = "gamma", ccov = treat) Number of subjects 4 Number of observations 20 Pareto distribution with renewal process gamma intensity with independence -Log likelihood 23.98151 Degrees of freedom 16 AIC 27.98151 Iterations 19 Location parameters estimate se (Intercept) -1.060 0.3784 treat 1.092 0.2637 Nonlinear parameters estimate se parameter initial -11.374 21.0866 0.0000115 shape 1.175 0.3213 3.2389484 Correlation matrix 1 2 3 4 1 1.000000 -0.312348 -0.009322 -0.878008 2 -0.312348 1.000000 -0.003881 -0.018661 3 -0.009322 -0.003881 1.000000 0.008582 4 -0.878008 -0.018661 0.008582 1.000000 > > > > cleanEx() > nameEx("km") > ### * km > > flush(stderr()); flush(stdout()) > > ### Name: km > ### Title: Kaplan-Meier Survivor Curves > ### Aliases: km plot.surv plot.km print.km plot.intensity.km plot.dist > ### plot.dist.km > ### Keywords: hplot > > ### ** Examples > > surv <- rgamma(40,2,scale=5) > cens <- rbinom(40,1,0.9) > treat <- gl(2,20) > plot(km(surv, cens, group=treat), main="",xlab="Months", + ylab="Probability of deterioration") > plot.dist(km(surv, cens, group=treat)) > plot.intensity(km(surv, cens, group=treat),ylab="Risk of deterioration") > > > > cleanEx() > nameEx("pbirth") > ### * pbirth > > flush(stderr()); flush(stdout()) > > ### Name: pbirth > ### Title: Fit Overdispersed Count Data as a Birth Process > ### Aliases: pbirth deviance.pbirth print.pbirth > ### Keywords: models > > ### ** Examples > > y <- rnbinom(100,2,0.6) > fr <- tabulate(y) > pbirth(fr, p=log(-log(0.7)), intensity="Poisson", type="series") Warning in log(prob1(p)) : NaNs produced Warning in nlm(like, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : -Inf replaced by maximally negative value Warning in log(prob1(p)) : NaNs produced Warning in nlm(like, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : -Inf replaced by maximally negative value Warning in log(prob1(p)) : NaNs produced Warning in nlm(like, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : -Inf replaced by maximally negative value Warning in log(prob1(p)) : NaNs produced Warning in nlm(like, p = p, hessian = TRUE, print.level = print.level, typsize = typsize, : -Inf replaced by maximally negative value Warning in sqrt(fitted.values) : NaNs produced Call: pbirth(fr, p = log(-log(0.7)), intensity = "Poisson", type = "series") Poisson intensity function: rep(exp(p[1]), length(nn)) -Log likelihood -1.797693e+308 AIC -1.797693e+308 Iterations 1 Coefficients: estimate se parameter p1 9.597 Inf NaN > pbirth(fr, p=c(log(-log(0.7)),log(5)), + intensity="negative binomial", type="series") Call: pbirth(fr, p = c(log(-log(0.7)), log(5)), intensity = "negative binomial", type = "series") negative binomial intensity function: exp(p[1]) * (exp(p[2]) + nn) -Log likelihood 63.15975 AIC 65.15975 Iterations 13 Coefficients: estimate se parameter p1 -0.2648 0.3749 0.5902 p2 -0.6707 0.4780 0.5114 Correlations: 1 2 1 1.0000 -0.8903 2 -0.8903 1.0000 > pbirth(fr, p=c(log(-log(0.7)),log(5),-1), + intensity="gen negative binomial", type="series") Call: pbirth(fr, p = c(log(-log(0.7)), log(5), -1), intensity = "gen negative binomial", type = "series") gen negative binomial intensity function: exp(p[1]) * (exp(p[2]) + nn)^(1 - exp(p[3])) -Log likelihood 0 AIC 3 Iterations 1 Coefficients: estimate se parameter p1 -15.491 NA 7.896e-17 p2 -21.586 NA 4.219e-10 p3 6.801 NA -8.976e+02 Correlations: 1 2 3 1 NA NA NA 2 NA NA NA 3 NA NA NA > > > > cleanEx() > nameEx("plot.intensity") > ### * plot.intensity > > flush(stderr()); flush(stdout()) > > ### Name: plot.intensity > ### Title: Plot Intensity Functions > ### Aliases: plot.intensity plot.intensity.default > ### Keywords: hplot > > ### ** Examples > > surv <- rgamma(40,2,scale=5) > cens <- rbinom(40,1,0.9) > treat <- gl(2,20) > plot(km(surv, cens, group=treat), main="",xlab="Months", + ylab="Probability of deterioration") > plot.dist(km(surv, cens, group=treat)) > plot.intensity(km(surv, cens, group=treat),ylab="Risk of deterioration") > > > > cleanEx() > nameEx("pp") > ### * pp > > flush(stderr()); flush(stdout()) > > ### Name: pp > ### Title: Create a Point Process Vector from Times between Events > ### Aliases: pp > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > py <- pp(y) > py [1] 0 0 0 0 1 0 0 1 0 1 0 0 0 1 > > > > cleanEx() > nameEx("survkit") > ### * survkit > > flush(stderr()); flush(stdout()) > > ### Name: survkit > ### Title: Weibull and Cox Models with Random Effects > ### Aliases: survkit baseline baseline.survivalkit print.survivalkit > ### residuals.survivalkit survival survival.survivalkit > ### Keywords: models > > ### ** Examples > > # y <- trunc(rweibull(20,2,20)) > y <- c(6,22,43,16,7,6,15,35,10,9,18,34,7,13,10,17,14,19,11,13) > # cens <- rbinom(20,1,0.9) > cens <- c(1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1) > id <- gl(2,10) > # x <- rnorm(20) > x <- c(1.82881379,1.06606868,0.70877744,-0.09932880,-0.60626148,-0.75371046, + 0.23884069,0.51199483,-0.73060095,-0.93222151,2.27947539,-0.73855454, + -0.36412735,-0.89122114,-0.05025962,-0.10001587,1.11460865,-1.87315971, + -0.11280052,-1.6880509) > # Kaplan-Meier estimates > survkit(y, censor=cens, model="Kaplan") ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C07CBC: log@@GLIBC_2.29 (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/./w_log_template.c:32) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C418DA: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:61) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C418E9: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:85) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B06: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:88) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B15: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:90) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B24: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:92) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Use of uninitialised value of size 8 ==2277988== at 0x4C41966: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:117) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Use of uninitialised value of size 8 ==2277988== at 0x4C4196F: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:117) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177ABA26: init_ (packages/tests-vg/event/src/survkit.f:871) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C07CBC: log@@GLIBC_2.29 (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/./w_log_template.c:32) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C418DA: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:61) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C418E9: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:85) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B06: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:88) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B15: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:90) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C41B24: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:92) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Use of uninitialised value of size 8 ==2277988== at 0x4C41966: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:117) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Use of uninitialised value of size 8 ==2277988== at 0x4C4196F: __ieee754_log_avx (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/../sysdeps/ieee754/dbl-64/e_log.c:117) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== Kaplan-Meier estimates with 95% interval and Nelson estimates ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x42F2E8: Rsqrt (svn/R-devel/src/main/arithmetic.c:1293) ==2277988== by 0x42F6E0: math1 (svn/R-devel/src/main/arithmetic.c:1271) ==2277988== by 0x42FE2C: do_math1 (svn/R-devel/src/main/arithmetic.c:1401) ==2277988== by 0x4E8E0B: bcEval_loop (svn/R-devel/src/main/eval.c:8183) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== by 0x53E890: Rf_usemethod (svn/R-devel/src/main/objects.c:513) ==2277988== by 0x53EAC2: do_usemethod (svn/R-devel/src/main/objects.c:579) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x42F6EC: math1 (svn/R-devel/src/main/arithmetic.c:1272) ==2277988== by 0x42FE2C: do_math1 (svn/R-devel/src/main/arithmetic.c:1401) ==2277988== by 0x4E8E0B: bcEval_loop (svn/R-devel/src/main/eval.c:8183) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== by 0x53E890: Rf_usemethod (svn/R-devel/src/main/objects.c:513) ==2277988== by 0x53EAC2: do_usemethod (svn/R-devel/src/main/objects.c:579) ==2277988== by 0x4E4E31: bcEval_loop (svn/R-devel/src/main/eval.c:8152) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x42FAB9: math1_ari (svn/R-devel/src/main/arithmetic.c:1229) ==2277988== by 0x42FE60: do_math1 (svn/R-devel/src/main/arithmetic.c:1405) ==2277988== by 0x4E8F0B: bcEval_loop (svn/R-devel/src/main/eval.c:8184) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F3CD6: forcePromise.part.0 (svn/R-devel/src/main/eval.c:976) ==2277988== by 0x4F3727: forcePromise (svn/R-devel/src/main/eval.c:956) ==2277988== by 0x4F3727: Rf_eval (svn/R-devel/src/main/eval.c:1193) ==2277988== by 0x4F3CD6: forcePromise.part.0 (svn/R-devel/src/main/eval.c:976) ==2277988== by 0x4F3727: forcePromise (svn/R-devel/src/main/eval.c:956) ==2277988== by 0x4F3727: Rf_eval (svn/R-devel/src/main/eval.c:1193) ==2277988== by 0x45AE81: do_bind (svn/R-devel/src/main/bind.c:1095) ==2277988== by 0x53BFD4: do_internal (svn/R-devel/src/main/names.c:1411) ==2277988== by 0x4E4E31: bcEval_loop (svn/R-devel/src/main/eval.c:8152) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== survival function lower upper cumulative hazard 6 0.90000 0.65602366 0.9740108 0.1000000 9 0.84375 0.58866167 0.9469836 0.1625000 10 0.73125 0.46838089 0.8788281 0.2958333 11 0.67500 0.41329536 0.8395960 0.3727564 13 0.56250 0.31142205 0.7529423 0.5394231 14 0.50625 0.26435743 0.7058928 0.6394231 15 0.45000 0.21983778 0.6564524 0.7505342 16 0.39375 0.17793481 0.6045916 0.8755342 17 0.33750 0.13880862 0.5501995 1.0183913 18 0.28125 0.10273396 0.4930644 1.1850580 19 0.22500 0.07015376 0.4328332 1.3850580 22 0.16875 0.04178889 0.3689335 1.6350580 34 0.11250 0.01888131 0.3004469 1.9683913 35 0.05625 0.00378828 0.2264022 2.4683913 43 0.00000 0.00000000 0.0000000 3.4683913 > # null Weibull model > survkit(y, censor=cens) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A3D21: fweib_ (packages/tests-vg/event/src/survkit.f:1556) ==2277988== by 0x177AA5B3: optimize_ (packages/tests-vg/event/src/survkit.f:472) ==2277988== by 0x177AC80E: weibull_ (packages/tests-vg/event/src/survkit.f:276) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AC80E: weibull_ (packages/tests-vg/event/src/survkit.f:276) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== Weibull model Call: survkit(y, censor = cens) -Log likelihood (null) 64.87871 AIC (null) 66.87871 -Log likelihood 64.87871 AIC 66.87871 Number of parameters 2 Number of events 18 Number censored 2 Number of iterations 35 Regression coefficients estimate se (Intercept) -5.697 1.061 Weibull power parameter estimate se 1 1.906 0.1683 Correlations: 1 2 1 1.000 -0.975 2 -0.975 1.000 > # one time-constant covariate > survkit(y, censor=cens, ccov=~x) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A3D21: fweib_ (packages/tests-vg/event/src/survkit.f:1556) ==2277988== by 0x177AA5B3: optimize_ (packages/tests-vg/event/src/survkit.f:472) ==2277988== by 0x177AD300: weibull_ (packages/tests-vg/event/src/survkit.f:397) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AD300: weibull_ (packages/tests-vg/event/src/survkit.f:397) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== Weibull model Call: survkit(y, censor = cens, ccov = ~x) -Log likelihood (null) 64.87871 AIC (null) 66.87871 -Log likelihood 64.55806 AIC 67.55806 Number of parameters 3 Number of events 18 Number censored 2 Number of iterations 59 Regression coefficients estimate se (Intercept) -5.8449 1.096 x -0.2021 0.252 Weibull power parameter estimate se 1 1.957 0.1702 Correlations: 1 2 3 1 1.0000 0.2154 -0.9766 2 0.2154 1.0000 -0.2178 3 -0.9766 -0.2178 1.0000 > # stratify > survkit(y, censor=cens, ccov=~x, strata=id) Weibull model Call: survkit(y, censor = cens, ccov = ~x, strata = id) -Log likelihood (null) 63.6416 AIC (null) 67.6416 -Log likelihood 63.62205 AIC 68.62205 Number of parameters 5 Number of events 18 Number censored 2 Number of strata 2 Number of iterations 53 Regression coefficients estimate se (Intercept)1 -4.86527 1.3478 (Intercept)2 -7.43421 1.8357 x -0.05619 0.2869 Weibull power parameter estimate se 1 1.616 0.2496 2 2.526 0.2297 Correlations: 1 2 3 4 5 1 1.000000 -0.005356 0.08162 -0.96398 0.01173 2 -0.005356 1.000000 -0.06562 0.01210 -0.98043 3 0.081621 -0.065617 1.00000 -0.18440 0.14375 4 -0.963983 0.012100 -0.18440 1.00000 -0.02651 5 0.011733 -0.980425 0.14375 -0.02651 1.00000 > # estimate a normal random effect > survkit(y, censor=cens, ccov=~x, random=id, dist="normal", + estimate=c(0.1,10,0.01), moments=TRUE) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A3D21: fweib_ (packages/tests-vg/event/src/survkit.f:1556) ==2277988== by 0x177AA5B3: optimize_ (packages/tests-vg/event/src/survkit.f:472) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779E91F: dfmin_ (packages/tests-vg/event/src/survkit.f:3851) ==2277988== by 0x177ACA6E: weibull_ (packages/tests-vg/event/src/survkit.f:311) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779E91F: dfmin_ (packages/tests-vg/event/src/survkit.f:3851) ==2277988== by 0x177ACA6E: weibull_ (packages/tests-vg/event/src/survkit.f:311) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A3D21: fweib_ (packages/tests-vg/event/src/survkit.f:1556) ==2277988== by 0x177AA5B3: optimize_ (packages/tests-vg/event/src/survkit.f:472) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779EC09: dfmin_ (packages/tests-vg/event/src/survkit.f:3915) ==2277988== by 0x177ACA6E: weibull_ (packages/tests-vg/event/src/survkit.f:311) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779EC09: dfmin_ (packages/tests-vg/event/src/survkit.f:3915) ==2277988== by 0x177ACA6E: weibull_ (packages/tests-vg/event/src/survkit.f:311) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A3D21: fweib_ (packages/tests-vg/event/src/survkit.f:1556) ==2277988== by 0x177AA5B3: optimize_ (packages/tests-vg/event/src/survkit.f:472) ==2277988== by 0x177ACD4C: weibull_ (packages/tests-vg/event/src/survkit.f:350) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177ACD4C: weibull_ (packages/tests-vg/event/src/survkit.f:350) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177ACFDC: weibull_ (packages/tests-vg/event/src/survkit.f:328) ==2277988== by 0x4AB6A3: do_dotCode (svn/R-devel/src/main/dotcode.c:2155) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== by 0x52A40D: Rf_mainloop (svn/R-devel/src/main/main.c:1242) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AC0BD: weibull_ (packages/tests-vg/event/src/survkit.f:35) ==2277988== Weibull model Call: survkit(y, censor = cens, ccov = ~x, random = id, dist = "normal", estimate = c(0.1, 10, 0.01), moments = TRUE) Warning in print.survivalkit(x) : algorithm did not converge -Log likelihood 62.25539 AIC 67.25539 Number of parameters 5 Number of events 18 Number censored 2 Number of iterations 2556 Normal random variance (mode) id 0.1039 mean sd skew moments 4.782e+09 2.518e+09 -1.21 Regression coefficients estimate se (Intercept) -5.8649 1.1235 x -0.1743 0.2674 Normal random effects estimate se id1 -0.04966 0.2895 id2 0.04966 0.2895 Weibull power parameter estimate se 1 1.964 0.1704 Correlations: 1 2 3 4 5 1 1.0000 0.1554 -0.11461 -0.20490 -0.95641 2 0.1554 1.0000 -0.22624 0.22624 -0.15619 3 -0.1146 -0.2262 1.00000 0.23995 -0.05332 4 -0.2049 0.2262 0.23995 1.00000 0.05332 5 -0.9564 -0.1562 -0.05332 0.05332 1.00000 > # try a fixed value for the normal random effect > survkit(y, censor=cens, ccov=~x, random=id, dist="normal", + estimate=1.3) Weibull model Call: survkit(y, censor = cens, ccov = ~x, random = id, dist = "normal", estimate = 1.3) -Log likelihood 64.73203 AIC 69.73203 Number of parameters 5 Number of events 18 Number censored 2 Number of iterations 62 Normal random variance (mode) id 1.3 Regression coefficients estimate se (Intercept) -5.8988 1.3723 x -0.1403 0.2813 Normal random effects estimate se id1 -0.1131 0.8493 id2 0.1131 0.8493 Weibull power parameter estimate se 1 1.975 0.1713 Correlations: 1 2 3 4 5 1 1.00000 0.06808 -0.52054 -0.59489 -0.79079 2 0.06808 1.00000 -0.15517 0.15517 -0.08173 3 -0.52054 -0.15517 1.00000 0.80243 -0.04825 4 -0.59489 0.15517 0.80243 1.00000 0.04825 5 -0.79079 -0.08173 -0.04825 0.04825 1.00000 > # estimate a log-gamma random effect > survkit(y, censor=cens, ccov=~x, random=id, dist="loggamma", + estimate=c(0.1,10,0.01)) Weibull model Call: survkit(y, censor = cens, ccov = ~x, random = id, dist = "loggamma", estimate = c(0.1, 10, 0.01)) -Log likelihood 64.07272 AIC 69.07272 Number of parameters 5 Number of events 18 Number censored 2 Number of iterations 20 Log gamma random variance (mode) id 9.996 Regression coefficients estimate se (Intercept) -5.8632 1.1219 x -0.1749 0.2672 Log gamma random effects estimate se id1 -0.04970 0.2903 id2 0.04735 0.2797 Weibull power parameter estimate se 1 1.964 0.1704 Correlations: 1 2 3 4 5 1 1.0000 0.1597 -0.11245 -0.1981 -0.95699 2 0.1597 1.0000 -0.23192 0.2184 -0.15752 3 -0.1125 -0.2319 1.00000 0.2331 -0.05435 4 -0.1981 0.2184 0.23313 1.0000 0.05120 5 -0.9570 -0.1575 -0.05435 0.0512 1.00000 > # estimate a log-gamma random effect by integrating it out > ## Not run: > ##D survkit(y, censor=cens, ccov=~x, dist="loggamma", estimate=1.3, > ##D integ=id, jointmode=TRUE) > ##D # try a fixed value of the log-gamma random effect, integrating it out > ##D survkit(y, censor=cens, ccov=~x, dist="loggamma", estimate=1, > ##D integ=id) > ## End(Not run) > # > # Cox model with one time-constant covariate > print(z <- survkit(y, censor=cens, ccov=~x, model="Cox", residuals=TRUE, + baseline=TRUE)) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C07CD3: log@@GLIBC_2.29 (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/./w_log_template.c:34) ==2277988== by 0x177AB0B1: init_ (packages/tests-vg/event/src/survkit.f:584) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x4F825C: do_set (svn/R-devel/src/main/eval.c:3581) ==2277988== by 0x4F37F2: Rf_eval (svn/R-devel/src/main/eval.c:1232) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4C07CD3: log@@GLIBC_2.29 (/usr/src/debug/glibc-2.39-38.fc40.x86_64/math/./w_log_template.c:34) ==2277988== by 0x177ABA3F: init_ (packages/tests-vg/event/src/survkit.f:876) ==2277988== by 0x177AD8EB: cox_ (packages/tests-vg/event/src/survkit.f:4753) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x4F825C: do_set (svn/R-devel/src/main/eval.c:3581) ==2277988== by 0x4F37F2: Rf_eval (svn/R-devel/src/main/eval.c:1232) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A077A: fcox_ (packages/tests-vg/event/src/survkit.f:5320) ==2277988== by 0x177ADA50: cox_ (packages/tests-vg/event/src/survkit.f:4807) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x4F825C: do_set (svn/R-devel/src/main/eval.c:3581) ==2277988== by 0x4F37F2: Rf_eval (svn/R-devel/src/main/eval.c:1232) ==2277988== by 0x4F3CD6: forcePromise.part.0 (svn/R-devel/src/main/eval.c:976) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AD733: cox_ (packages/tests-vg/event/src/survkit.f:4630) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A077A: fcox_ (packages/tests-vg/event/src/survkit.f:5320) ==2277988== by 0x177AA6BE: optimize_ (packages/tests-vg/event/src/survkit.f:475) ==2277988== by 0x177AE300: cox_ (packages/tests-vg/event/src/survkit.f:4823) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x4F825C: do_set (svn/R-devel/src/main/eval.c:3581) ==2277988== by 0x4F37F2: Rf_eval (svn/R-devel/src/main/eval.c:1232) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AE300: cox_ (packages/tests-vg/event/src/survkit.f:4823) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x4F825C: do_set (svn/R-devel/src/main/eval.c:3581) ==2277988== by 0x4F37F2: Rf_eval (svn/R-devel/src/main/eval.c:1232) ==2277988== by 0x4F3CD6: forcePromise.part.0 (svn/R-devel/src/main/eval.c:976) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== Cox model Call: survkit(y, censor = cens, ccov = ~x, model = "Cox", residuals = TRUE, baseline = TRUE) -Log likelihood (null) 36.81933 AIC (null) 36.81933 -Log likelihood 36.53566 AIC 37.53566 Number of parameters 1 Number of events 18 Number censored 2 Number of iterations 5 Regression coefficients estimate se x -0.1753 0.2331 > residuals(z) time censor stratum generalized martingale deviance [1,] 6 1 1 0.07256743 0.92743257 1.84163325 [2,] 7 0 1 1.35629912 -0.35629912 -0.32105876 [3,] 7 0 1 3.06307042 -2.06307042 -1.37379227 [4,] 9 1 1 0.89091583 0.10908417 0.11332390 [5,] 10 1 1 0.11121538 -0.11121538 -0.47162566 [6,] 10 1 1 0.11412811 0.88587189 1.60284860 [7,] 11 1 1 0.71975308 0.28024692 0.31176962 [8,] 13 1 1 2.25645803 -1.25645803 -0.94091624 [9,] 13 1 1 0.33626372 0.66373628 0.92317200 [10,] 14 1 1 0.19135465 0.80864535 1.29998570 [11,] 15 1 1 0.79462993 0.20537007 0.22139874 [12,] 16 1 1 2.24052598 -1.24052598 -0.93146694 [13,] 17 1 1 0.10659262 -0.10659262 -0.46171986 [14,] 18 1 1 0.63065687 0.36934313 0.42813601 [15,] 19 1 1 0.29845181 0.70154819 1.00756996 [16,] 22 1 1 1.03640758 -0.03640758 -0.03597489 [17,] 34 1 1 0.52591367 0.47408633 0.58057192 [18,] 35 1 1 1.92354797 -0.92354797 -0.73399808 [19,] 43 1 1 0.72521894 0.27478106 0.30496105 > baseline(z) cumulative hazard survival function 6 0.1000000 0.90483742 9 0.1625000 0.85001609 10 0.2958333 0.74391140 11 0.3727564 0.68883301 13 0.5394231 0.58308455 14 0.6394231 0.52759672 15 0.7505342 0.47211429 16 0.8755342 0.41663940 17 1.0183913 0.36117548 18 1.1850580 0.30572845 19 1.3850580 0.25030928 22 1.6350580 0.19494106 34 1.9683913 0.13968138 35 2.4683913 0.08472104 43 3.4683913 0.03116713 > # obtain the quantiles > print(z <- survkit(y, censor=cens, ccov=~x, model="Cox", + survival="quantiles", svalues=seq(10,90,by=10))) Cox model Call: survkit(y, censor = cens, ccov = ~x, model = "Cox", survival = "quantiles", svalues = seq(10, 90, by = 10)) -Log likelihood (null) 36.81933 AIC (null) 36.81933 -Log likelihood 36.53566 AIC 37.53566 Number of parameters 1 Number of events 18 Number censored 2 Number of iterations 5 Regression coefficients estimate se x -0.1753 0.2331 > survival(z) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4FCCA6: Rf_formatReal (svn/R-devel/src/main/format.c:445) ==2277988== by 0x566059: printRealMatrix (svn/R-devel/src/main/printarray.c:244) ==2277988== by 0x5677C5: Rf_printMatrix (svn/R-devel/src/main/printarray.c:365) ==2277988== by 0x5625E7: Rf_PrintValueRec (svn/R-devel/src/main/print.c:941) ==2277988== by 0x562ABA: do_printdefault (svn/R-devel/src/main/print.c:320) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4FCCB0: scientific (svn/R-devel/src/main/format.c:328) ==2277988== by 0x4FCCB0: Rf_formatReal (svn/R-devel/src/main/format.c:453) ==2277988== by 0x566059: printRealMatrix (svn/R-devel/src/main/printarray.c:244) ==2277988== by 0x5677C5: Rf_printMatrix (svn/R-devel/src/main/printarray.c:365) ==2277988== by 0x5625E7: Rf_PrintValueRec (svn/R-devel/src/main/print.c:941) ==2277988== by 0x562ABA: do_printdefault (svn/R-devel/src/main/print.c:320) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x4FCCB2: scientific (svn/R-devel/src/main/format.c:328) ==2277988== by 0x4FCCB2: Rf_formatReal (svn/R-devel/src/main/format.c:453) ==2277988== by 0x566059: printRealMatrix (svn/R-devel/src/main/printarray.c:244) ==2277988== by 0x5677C5: Rf_printMatrix (svn/R-devel/src/main/printarray.c:365) ==2277988== by 0x5625E7: Rf_PrintValueRec (svn/R-devel/src/main/print.c:941) ==2277988== by 0x562ABA: do_printdefault (svn/R-devel/src/main/print.c:320) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== time S(t) 1 ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x56B010: Rf_EncodeReal0 (svn/R-devel/src/main/printutils.c:208) ==2277988== by 0x56626D: printRealMatrix (svn/R-devel/src/main/printarray.c:247) ==2277988== by 0x5677C5: Rf_printMatrix (svn/R-devel/src/main/printarray.c:365) ==2277988== by 0x5625E7: Rf_PrintValueRec (svn/R-devel/src/main/print.c:941) ==2277988== by 0x562ABA: do_printdefault (svn/R-devel/src/main/print.c:320) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x56B016: Rf_EncodeReal0 (svn/R-devel/src/main/printutils.c:208) ==2277988== by 0x56626D: printRealMatrix (svn/R-devel/src/main/printarray.c:247) ==2277988== by 0x5677C5: Rf_printMatrix (svn/R-devel/src/main/printarray.c:365) ==2277988== by 0x5625E7: Rf_PrintValueRec (svn/R-devel/src/main/print.c:941) ==2277988== by 0x562ABA: do_printdefault (svn/R-devel/src/main/print.c:320) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F68B8: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x53E22B: dispatchMethod (svn/R-devel/src/main/objects.c:473) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x1779C99A: baseline_ (packages/tests-vg/event/src/survkit.f:5937) ==2277988== 0 0.9 1 0 0.8 1 0 0.7 1 0 0.6 1 0 0.5 1 0 0.4 1 0 0.3 1 0 0.2 1 0 0.1 2 9 0.9 2 10 0.8 2 13 0.7 2 14 0.6 2 16 0.5 2 18 0.4 2 22 0.3 2 0 0.2 2 0 0.1 3 9 0.9 3 10 0.8 3 13 0.7 3 14 0.6 3 16 0.5 3 18 0.4 3 19 0.3 3 34 0.2 3 43 0.1 4 9 0.9 4 10 0.8 4 11 0.7 4 13 0.6 4 15 0.5 4 0 0.4 4 0 0.3 4 0 0.2 4 0 0.1 5 6 0.9 5 0 0.8 5 0 0.7 5 0 0.6 5 0 0.5 5 0 0.4 5 0 0.3 5 0 0.2 5 0 0.1 6 6 0.9 6 0 0.8 6 0 0.7 6 0 0.6 6 0 0.5 6 0 0.4 6 0 0.3 6 0 0.2 6 0 0.1 7 9 0.9 7 10 0.8 7 11 0.7 7 13 0.6 7 15 0.5 7 0 0.4 7 0 0.3 7 0 0.2 7 0 0.1 8 9 0.9 8 10 0.8 8 13 0.7 8 14 0.6 8 16 0.5 8 17 0.4 8 19 0.3 8 34 0.2 8 0 0.1 9 6 0.9 9 10 0.8 9 0 0.7 9 0 0.6 9 0 0.5 9 0 0.4 9 0 0.3 9 0 0.2 9 0 0.1 10 6 0.9 10 0 0.8 10 0 0.7 10 0 0.6 10 0 0.5 10 0 0.4 10 0 0.3 10 0 0.2 10 0 0.1 11 9 0.9 11 11 0.8 11 13 0.7 11 16 0.6 11 18 0.5 11 0 0.4 11 0 0.3 11 0 0.2 11 0 0.1 12 6 0.9 12 10 0.8 12 11 0.7 12 13 0.6 12 14 0.5 12 16 0.4 12 18 0.3 12 22 0.2 12 0 0.1 13 6 0.9 13 0 0.8 13 0 0.7 13 0 0.6 13 0 0.5 13 0 0.4 13 0 0.3 13 0 0.2 13 0 0.1 14 6 0.9 14 10 0.8 14 11 0.7 14 13 0.6 14 0 0.5 14 0 0.4 14 0 0.3 14 0 0.2 14 0 0.1 15 9 0.9 15 10 0.8 15 0 0.7 15 0 0.6 15 0 0.5 15 0 0.4 15 0 0.3 15 0 0.2 15 0 0.1 16 9 0.9 16 10 0.8 16 11 0.7 16 13 0.6 16 15 0.5 16 17 0.4 16 0 0.3 16 0 0.2 16 0 0.1 17 9 0.9 17 10 0.8 17 13 0.7 17 14 0.6 17 0 0.5 17 0 0.4 17 0 0.3 17 0 0.2 17 0 0.1 18 6 0.9 18 9 0.8 18 10 0.7 18 11 0.6 18 13 0.5 18 15 0.4 18 16 0.3 18 18 0.2 18 0 0.1 19 9 0.9 19 10 0.8 19 11 0.7 19 0 0.6 19 0 0.5 19 0 0.4 19 0 0.3 19 0 0.2 19 0 0.1 20 6 0.9 20 10 0.8 20 10 0.7 20 13 0.6 20 13 0.5 20 0 0.4 20 0 0.3 20 0 0.2 20 0 0.1 > # estimate a log-gamma random effect > survkit(y, censor=cens, ccov=~x, model="Cox", random=id, + dist="loggamma", estimate=c(0.1,10,0.01)) ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A077A: fcox_ (packages/tests-vg/event/src/survkit.f:5320) ==2277988== by 0x177AA6BE: optimize_ (packages/tests-vg/event/src/survkit.f:475) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779E91F: dfmin_ (packages/tests-vg/event/src/survkit.f:3851) ==2277988== by 0x177ADC6B: cox_ (packages/tests-vg/event/src/survkit.f:4838) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779E91F: dfmin_ (packages/tests-vg/event/src/survkit.f:3851) ==2277988== by 0x177ADC6B: cox_ (packages/tests-vg/event/src/survkit.f:4838) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A077A: fcox_ (packages/tests-vg/event/src/survkit.f:5320) ==2277988== by 0x177AA6BE: optimize_ (packages/tests-vg/event/src/survkit.f:475) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779EC09: dfmin_ (packages/tests-vg/event/src/survkit.f:3915) ==2277988== by 0x177ADC6B: cox_ (packages/tests-vg/event/src/survkit.f:4838) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177AA987: ftomin_ (packages/tests-vg/event/src/survkit.f:982) ==2277988== by 0x1779EC09: dfmin_ (packages/tests-vg/event/src/survkit.f:3915) ==2277988== by 0x177ADC6B: cox_ (packages/tests-vg/event/src/survkit.f:4838) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177A077A: fcox_ (packages/tests-vg/event/src/survkit.f:5320) ==2277988== by 0x177AA6BE: optimize_ (packages/tests-vg/event/src/survkit.f:475) ==2277988== by 0x177ADD1E: cox_ (packages/tests-vg/event/src/survkit.f:4918) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== ==2277988== Conditional jump or move depends on uninitialised value(s) ==2277988== at 0x177AA6ED: optimize_ (packages/tests-vg/event/src/survkit.f:489) ==2277988== by 0x177ADD1E: cox_ (packages/tests-vg/event/src/survkit.f:4918) ==2277988== by 0x4AB50C: do_dotCode (svn/R-devel/src/main/dotcode.c:2193) ==2277988== by 0x4E514C: bcEval_loop (svn/R-devel/src/main/eval.c:8132) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7515) ==2277988== by 0x4F3157: bcEval (svn/R-devel/src/main/eval.c:7500) ==2277988== by 0x4F348A: Rf_eval (svn/R-devel/src/main/eval.c:1167) ==2277988== by 0x4F520D: R_execClosure (svn/R-devel/src/main/eval.c:2389) ==2277988== by 0x4F5EC6: applyClosure_core (svn/R-devel/src/main/eval.c:2302) ==2277988== by 0x4F3595: Rf_applyClosure (svn/R-devel/src/main/eval.c:2324) ==2277988== by 0x4F3595: Rf_eval (svn/R-devel/src/main/eval.c:1280) ==2277988== by 0x529F4B: Rf_ReplIteration (svn/R-devel/src/main/main.c:264) ==2277988== by 0x52A32F: R_ReplConsole (svn/R-devel/src/main/main.c:317) ==2277988== by 0x52A3C4: run_Rmainloop (svn/R-devel/src/main/main.c:1235) ==2277988== Uninitialised value was created by a stack allocation ==2277988== at 0x177AA4D3: optimize_ (packages/tests-vg/event/src/survkit.f:432) ==2277988== Cox model Call: survkit(y, censor = cens, ccov = ~x, model = "Cox", random = id, dist = "loggamma", estimate = c(0.1, 10, 0.01)) -Log likelihood 36.0801 AIC 39.0801 Number of parameters 3 Number of events 18 Number censored 2 Number of iterations 2 Log gamma random variance (mode) id 9.996 Regression coefficients estimate se x -0.1662 0.2427 Log gamma random effects estimate se id1 -0.02241 0.2872 id2 0.02192 0.2823 > > > > cleanEx() > nameEx("tccov") > ### * tccov > > flush(stderr()); flush(stdout()) > > ### Name: tccov > ### Title: Create a Vector of Time-constant Covariates for a Point Process > ### Aliases: tccov > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > id <- c(1,1,2,2) > x <- c(5.2,3.1) > xcov <- tccov(y, x, id) > xcov [1] 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 3.1 3.1 3.1 3.1 3.1 3.1 > > > > cleanEx() > nameEx("tpast") > ### * tpast > > flush(stderr()); flush(stdout()) > > ### Name: tpast > ### Title: Create a Vector of Times Past since Previous Events for a Point > ### Process > ### Aliases: tpast > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > ptime <- tpast(y) > ptime [1] 1 2 3 4 5 1 2 3 1 2 1 2 3 4 > > > > cleanEx() > nameEx("ttime") > ### * ttime > > flush(stderr()); flush(stdout()) > > ### Name: ttime > ### Title: Create a Vector of Total Time Elapsed for each Individual for a > ### Point Process > ### Aliases: ttime > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > id <- c(1,1,2,2) > itime <- ttime(y, id) > itime [1] 1 2 3 4 5 6 7 8 1 2 3 4 5 6 > > > > cleanEx() > nameEx("tvcov") > ### * tvcov > > flush(stderr()); flush(stdout()) > > ### Name: tvcov > ### Title: Create a Vector of Time-varying Covariates for a Point Process > ### Aliases: tvcov > ### Keywords: manip > > ### ** Examples > > y <- c(5,3,2,4) > x <- c(1,2,2,1,2,2,1) > tx <- c(2,3,1,2,2,2,2) > zcov <- tvcov(y, x, tx) > zcov [1] 1 1 2 2 2 2 1 1 2 2 2 2 1 1 > > > > ### *