* using log directory ‘/Users/ripley/R/packages/tests-devel/aods3.Rcheck’ * using R Under development (unstable) (2024-04-17 r86441) * using platform: aarch64-apple-darwin23.4.0 * R was compiled by Apple clang version 15.0.0 (clang-1500.3.9.4) GNU Fortran (GCC) 12.2.0 * running under: macOS Sonoma 14.4.1 * using session charset: UTF-8 * using option ‘--no-stop-on-test-error’ * checking for file ‘aods3/DESCRIPTION’ ... OK * this is package ‘aods3’ version ‘0.4-1.2’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for executable files ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘aods3’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) gof.Rd:32: Lost braces 32 | Assuming that the data length is \eqn{N} and the number of the parameters in the model is \eqn{p}, eqn{D} and eqn{X^2} are compared to a chi-squared distribution with \eqn{N-p} degrees of freedom. | ^ checkRd: (-1) gof.Rd:32: Lost braces 32 | Assuming that the data length is \eqn{N} and the number of the parameters in the model is \eqn{p}, eqn{D} and eqn{X^2} are compared to a chi-squared distribution with \eqn{N-p} degrees of freedom. | ^ checkRd: (-1) iccbin.Rd:23: Lost braces 23 | \item{m}{A vector of the numbers of successes (proportions are eqn{y = m / n}).} | ^ checkRd: (-1) varbin.Rd:22: Lost braces 22 | \item{m}{A vector of the numbers of successes (proportions are eqn{y = m / n}).} | ^ * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking LazyData ... OK * checking data for ASCII and uncompressed saves ... OK * checking examples ... ERROR Running examples in ‘aods3-Ex.R’ failed The error most likely occurred in: > ### Name: aodml > ### Title: ML Estimation of Generalized Linear Models for Overdispersed > ### Count Data > ### Aliases: aodml print.aodml summary.aodml print.summary.aodml > ### anova.aodml print.anova.aodml fitted.aodml residuals.aodml coef.aodml > ### logLik.aodml deviance.aodml df.residual.aodml AIC.aodml vcov.aodml > ### predict.aodml > ### Keywords: regression > > ### ** Examples > > > #------ Beta-binomial model > > data(orob2) > fm1 <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb") Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced > > # summaries > fm1 $call aodml(formula = cbind(m, n - m) ~ seed, data = orob2, family = "bb") $b (Intercept) seedO75 -0.2601209 0.4128158 $phi phi.(Intercept) 0.07804472 $phi.scale [1] "identity" $varparam (Intercept) seedO75 phi.(Intercept) (Intercept) 0.0511613216 -0.051370647 -0.0006190502 seedO75 -0.0513706469 0.089589078 0.0009264330 phi.(Intercept) -0.0006190502 0.000926433 0.0009090414 $logL [1] -63.5527 $iterations function gradient 32 7 $code [1] 0 > summary(fm1) Call: aodml(formula = cbind(m, n - m) ~ seed, data = orob2, family = "bb") Convergence was obtained after 327 iterations. Mu coefficients: Estimate Std. Error z value Pr(> |z|) (Intercept) -0.2601 0.2262 -1.1500 0.2501 seedO75 0.4128 0.2993 1.3792 0.1678 Phi coefficients: (scale = identity) Estimate Std. Error phi.(Intercept) 0.07804 0.03015 Log-likelihood statistics Log-lik df.model df.resid Deviance AIC AICc -63.55 3 18 22 133.1 134.5 > coef(fm1) (Intercept) seedO75 -0.2601209 0.4128158 > vcov(fm1) (Intercept) seedO75 (Intercept) 0.05116132 -0.05137065 seedO75 -0.05137065 0.08958908 > logLik(fm1) 'log Lik.' -63.5527 (df=3) > deviance(fm1) [1] 21.99571 > AIC(fm1) nobs df.model AIC AICc fm1 21 3 133.1054 134.5172 > gof(fm1) D = 21.9957, df = 18, P(>D) = 0.2321757 X2 = 21.8555, df = 18, P(>X2) = 0.2384633 > > # predictions > cbind( + fitted(fm1), + fitted(fm1, what = "nu"), + fitted(fm1, what = "eta"), + fitted(fm1, what = "phi") + ) [,1] [,2] [,3] [,4] [1,] 0.5380997 0.1526949 0.1526949 0.07804472 [2,] 0.5380997 0.1526949 0.1526949 0.07804472 [3,] 0.5380997 0.1526949 0.1526949 0.07804472 [4,] 0.5380997 0.1526949 0.1526949 0.07804472 [5,] 0.5380997 0.1526949 0.1526949 0.07804472 [6,] 0.5380997 0.1526949 0.1526949 0.07804472 [7,] 0.5380997 0.1526949 0.1526949 0.07804472 [8,] 0.5380997 0.1526949 0.1526949 0.07804472 [9,] 0.5380997 0.1526949 0.1526949 0.07804472 [10,] 0.5380997 0.1526949 0.1526949 0.07804472 [11,] 0.5380997 0.1526949 0.1526949 0.07804472 [12,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [13,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [14,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [15,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [16,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [17,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [18,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [19,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [20,] 0.4353340 -0.2601209 -0.2601209 0.07804472 [21,] 0.4353340 -0.2601209 -0.2601209 0.07804472 > predict(fm1, type = "response", se.fit = TRUE) $fit [1] 0.5380997 0.5380997 0.5380997 0.5380997 0.5380997 0.5380997 0.5380997 [8] 0.5380997 0.5380997 0.5380997 0.5380997 0.4353340 0.4353340 0.4353340 [15] 0.4353340 0.4353340 0.4353340 0.4353340 0.4353340 0.4353340 0.4353340 $se.fit [1] 0.04845681 0.04845681 0.04845681 0.04845681 0.04845681 0.04845681 [7] 0.04845681 0.04845681 0.04845681 0.04845681 0.04845681 0.05560132 [13] 0.05560132 0.05560132 0.05560132 0.05560132 0.05560132 0.05560132 [19] 0.05560132 0.05560132 0.05560132 > newdat <- data.frame(seed = c("O73", "O75")) > predict(fm1, type = "response", se.fit = TRUE, newdata = newdat) $fit [1] 0.4353340 0.5380997 $se.fit [1] 0.05560132 0.04845681 > > # model with heterogeneity in phi > fm <- aodml(cbind(m, n - m) ~ seed, data = orob2, + family = "bb", phi.formula = ~ seed) Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced > summary(fm) Call: aodml(formula = cbind(m, n - m) ~ seed, data = orob2, family = "bb", phi.formula = ~seed) Convergence was obtained after 4312 iterations. Mu coefficients: Estimate Std. Error z value Pr(> |z|) (Intercept) -0.2097 0.1816 -1.1544 0.2483 seedO75 0.3700 0.2839 1.3033 0.1925 Phi coefficients: (scale = identity) Estimate Std. Error phi.seedO73 0.03082 0.03076 phi.seedO75 0.1046 0.04758 Log-likelihood statistics Log-lik df.model df.resid Deviance AIC AICc -62.77 4 17 22.56 133.5 136 > AIC(fm1, fm) nobs df.model AIC AICc fm1 21 3 133.1054 134.5172 fm 21 4 133.5336 136.0336 > > # various phi scales > fm <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb") Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced > fm$phi phi.(Intercept) 0.07804472 > fm$phi.scale [1] "identity" > fm <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb", + phi.scale = "log") > fm$phi phi.(Intercept) -2.550548 > fm$phi.scale [1] "log" > fm <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb", + phi.scale = "inverse") > fm$phi phi.(Intercept) 12.814 > fm$phi.scale [1] "inverse" > > ### Models with coefficient(s) set as constant > > # model with 1 phi coefficient, set as constant "0.02" > fm <- aodml(formula = cbind(m, n - m) ~ seed * root, data = orob2, + family = "bb", fixpar = list(5, 0.02)) > fm$param (Intercept) seedO75 rootCUCUMBER -0.45728115 -0.07866257 0.51270609 seedO75:rootCUCUMBER phi.(Intercept) 0.80669498 0.02000000 > fm$varparam (Intercept) seedO75 rootCUCUMBER seedO75:rootCUCUMBER (Intercept) 0.05487993 -0.05487993 -0.05487993 0.05487993 seedO75 -0.05487993 0.08804602 0.05487993 -0.08804602 rootCUCUMBER -0.05487993 0.05487993 0.10270935 -0.10270935 seedO75:rootCUCUMBER 0.05487993 -0.08804602 -0.10270935 0.17105361 phi.(Intercept) NA NA NA NA phi.(Intercept) (Intercept) NA seedO75 NA rootCUCUMBER NA seedO75:rootCUCUMBER NA phi.(Intercept) NA > > # model with 2 phi coefficients, with the first set as constant ~ "0" > fm <- aodml(formula = cbind(m, n - m) ~ seed * root, data = orob2, + family = "bb", phi.formula = ~ seed, fixpar = list(5, 1e-15)) Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced > fm$param (Intercept) seedO75 rootCUCUMBER -2.674541e-01 -2.027569e-01 5.405620e-01 seedO75:rootCUCUMBER phi.seedO73 phi.seedO75 7.505806e-01 1.000000e-15 4.297397e-03 > fm$varparam (Intercept) seedO75 rootCUCUMBER (Intercept) 6.400000e-06 -0.0000064000 -6.400000e-06 seedO75 -6.400000e-06 0.0203950770 6.400000e-06 rootCUCUMBER -6.400000e-06 0.0000064000 1.440000e-05 seedO75:rootCUCUMBER 6.400000e-06 -0.0194415500 -1.440000e-05 phi.seedO73 NA NA NA phi.seedO75 -1.420943e-22 0.0002206495 1.431205e-22 seedO75:rootCUCUMBER phi.seedO73 phi.seedO75 (Intercept) 6.400000e-06 NA -1.355574e-21 seedO75 -1.944155e-02 NA 2.206495e-04 rootCUCUMBER -1.440000e-05 NA 1.383714e-21 seedO75:rootCUCUMBER 3.990851e-02 NA -2.834833e-05 phi.seedO73 NA NA NA phi.seedO75 -2.834833e-05 NA 4.449918e-05 > > # model with 2 phi coefficients, with the first set as constant ~ "0", > # and the mu intercept (1rst coef of vector b) set as as constant "-0.5" > fm <- aodml(formula = cbind(m, n - m) ~ seed * root, data = orob2, + family = "bb", phi.formula = ~ seed, + fixpar = list(c(1, 5), c(-0.5, 1e-15))) Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Warning in lbeta(a + m, b + n - m) : NaNs produced Warning in lbeta(a, b) : NaNs produced Error in optim(par = param.start[id.est], fn = m.logL, hessian = hessian, : non-finite finite-difference value [4] Calls: aodml -> optim Execution halted * checking PDF version of manual ... OK * checking HTML version of manual ... OK * checking for detritus in the temp directory ... OK * DONE Status: 1 ERROR, 1 NOTE See ‘/Users/ripley/R/packages/tests-devel/aods3.Rcheck/00check.log’ for details. 12.76 real 9.66 user 2.50 sys