* using log directory ‘/data/gannet/ripley/R/packages/tests-Suggests/gamboostLSS.Rcheck’
* using R Under development (unstable) (2025-12-22 r89219)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2)
    GNU Fortran (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2)
* running under: Fedora Linux 42 (Workstation Edition)
* using session charset: UTF-8
* using option ‘--no-stop-on-test-error’
* checking for file ‘gamboostLSS/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘gamboostLSS’ version ‘2.1-0’
* 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 ‘gamboostLSS’ can be installed ... [18s/51s] OK
* checking package directory ... OK
* checking ‘build’ 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 ... [4s/11s] 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 whether startup messages can be suppressed ... 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 ... [32s/45s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... 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 sizes of PDF files under ‘inst/doc’ ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘gamboostLSS-Ex.R’ failed
The error most likely occurred in:

> ### Name: as.families
> ### Title: Include 'gamlss' families in the boosting framework of
> ###   'gamboostLSS'
> ### Aliases: as.families gamlss.Families gamlss1parMu gamlss2parMu
> ###   gamlss2parSigma gamlss3parMu gamlss3parSigma gamlss3parNu
> ###   gamlss4parMu gamlss4parSigma gamlss4parNu gamlss4parTau
> ### Keywords: models distributions
> 
> ### ** Examples
> 
> ## simulate small example
> set.seed(123)
> x <- runif(1000)
> 
> y <- rnorm(mean = 2 + 3 * x,        # effect on mu
+            sd   = exp( 1 - 1 * x ), # effect on sigma
+            n    = 1000)
> 
> ## boosting
> glmss <- glmboostLSS(y ~ x, families = as.families("NO"))
Error in as.families("NO") : 
  Please install package 'gamlss.dist' for using gamlss families.
Calls: glmboostLSS -> mboostLSS_fit -> as.families
Execution halted
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘bugfixes.R’ [5s/11s]
  Running ‘regtest-families.R’
  Running ‘regtest-gamboostLSS.R’ [10s/18s]
  Running ‘regtest-glmboostLSS.R’ [4s/10s]
  Running ‘regtest-mstop.R’ [6s/12s]
  Running ‘regtest-noncyclic_fitting.R’ [15s/20s]
  Running ‘regtest-stabilization.R’ [14s/25s]
  Running ‘regtest-stabsel.R’ [14s/17s]
 [73s/123s] ERROR
Running the tests in ‘tests/bugfixes.R’ failed.
Complete output:
  > ###
  > # Bugfixes
  > 
  > require("gamboostLSS")
  Loading required package: gamboostLSS
  Loading required package: mboost
  Loading required package: parallel
  Loading required package: stabs
  
  Attaching package: 'gamboostLSS'
  
  The following object is masked from 'package:stats':
  
      model.weights
  
  > require("gamlss")
  Loading required package: gamlss
  Warning message:
  In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
    there is no package called 'gamlss'
  > 
  > ## subset method was missing if initial mstop = 1
  > set.seed(1907)
  > x1 <- rnorm(1000)
  > x2 <- rnorm(1000)
  > x3 <- rnorm(1000)
  > x4 <- rnorm(1000)
  > x5 <- rnorm(1000)
  > x6 <- rnorm(1000)
  > mu    <- exp(1.5 + x1^2 +0.5 * x2 - 3 * sin(x3) -1 * x4)
  > sigma <- exp(-0.2 * x4 +0.2 * x5 +0.4 * x6)
  > y <- numeric(1000)
  > for( i in 1:1000)
  +     y[i] <- rnbinom(1, size = sigma[i], mu = mu[i])
  > dat <- data.frame(x1, x2, x3, x4, x5, x6, y)
  > 
  > model <- gamboostLSS(y ~ ., families = NBinomialLSS(), data = dat,
  +                      control = boost_control(mstop = 1))
  > model[10]
  
  	 LSS Models fitted via Model-based Boosting
  
  Call:
  gamboostLSS(formula = y ~ ., data = dat, families = NBinomialLSS(),     control = boost_control(mstop = 1))
  
  Number of boosting iterations (mstop):  mu = 10, sigma = 10 
  Step size:  mu = 0.1, sigma = 0.1 
  
  Families:
  
  	 Negative Negative-Binomial Likelihood: mu (log link) 
  
  Loss function: -(lgamma(y + sigma) - lgamma(sigma) - lgamma(y + 1) + sigma *  
       log(sigma) + y * f - (y + sigma) * log(exp(f) + sigma)) 
   
  
  	 Negative Negative-Binomial Likelihood: sigma (log link) 
  
  Loss function: -(lgamma(y + exp(f)) - lgamma(exp(f)) - lgamma(y + 1) + exp(f) *  
       f + y * log(mu) - (y + exp(f)) * log(mu + exp(f))) 
   
  > 
  > 
  > ## selected() was broken (didn't call mboost-function)
  > stopifnot(all.equal(selected(model),
  +                     list(mu = mboost::selected(model[[1]]),
  +                          sigma = mboost::selected(model[[2]]))))
  > 
  > # If the families argument is not specified explicitly in mboostLSS one gets an
  > # error in cvrisk.mboostLSS() (spotted by Almond Stöcker).
  > # (https://github.com/boost-R/gamboostLSS/issues/9)
  > set.seed(1907)
  > x1 <- rnorm(1000)
  > mu    <- 2*x1
  > sigma <- rep(1, 1000)
  > y <- numeric(1000)
  > for( i in 1:1000)
  +        y[i] <- rnorm(1, mean = mu[i], sd=sigma[i])
  > dat <- data.frame(x1=x1, y=y)
  > ## model with default families
  > model <- mboostLSS(y ~ bbs(x1), data = dat, control = boost_control(mstop = 2))
  > ## cvrisk.mboostLSS() does not work as families was not specified in model call
  > cvr <- try(cvrisk(model, folds = cv(model.weights(model), B=3), trace=FALSE),
  +            silent = TRUE)
  Warning message:
  In make.grid(mstop(object)) :
    Duplicates produced; Only unique values are returned
  > if (inherits(cvr, "try-error"))
  +     stop("cvrisk does not work if no family was (explicitly) chosen")
  > 
  > 
  > # Make sure that gamlss.dist::BB and gamlss.dist::BI work (spotted by F. Scheipl)
  > # (https://github.com/boost-R/gamboostLSS/issues/12)
  > set.seed(123)
  > n <- 100
  > x <- rnorm(n)
  > z <- rnorm(n)
  > data <- data.frame(y = rbinom(n, p = plogis(x + z), size = 60), x = x, z= z)
  > data$ymat <- with(data, cbind(success = data$y, fail = 60 - data$y))
  > 
  > m1 <- gamlss(ymat ~ x + z, data = data, family = BB)
  Error in gamlss(ymat ~ x + z, data = data, family = BB) : 
    could not find function "gamlss"
  Execution halted
Running the tests in ‘tests/regtest-families.R’ failed.
Complete output:
  > ###
  > # check families
  > 
  > require("gamboostLSS")
  Loading required package: gamboostLSS
  Loading required package: mboost
  Loading required package: parallel
  Loading required package: stabs
  
  Attaching package: 'gamboostLSS'
  
  The following object is masked from 'package:stats':
  
      model.weights
  
  > require("gamlss")
  Loading required package: gamlss
  Warning message:
  In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
    there is no package called 'gamlss'
  > 
  > 
  > ### check families with only one offset specified (other to choose via optim)
  > set.seed(1907)
  > n <- 5000
  > x1  <- runif(n)
  > x2 <- runif(n)
  > mu <- 2 -1*x1 - 3*x2
  > sigma <- exp(-1*x1 + 3*x2)
  > df <- exp(1 + 3*x1 + 1*x2)
  > y <- rTF(n = n, mu = mu, sigma = sigma, nu = df)
  Error in rTF(n = n, mu = mu, sigma = sigma, nu = df) : 
    could not find function "rTF"
  Execution halted
Running the tests in ‘tests/regtest-glmboostLSS.R’ failed.
Complete output:
  > ###
  > # check glmboostLSS()
  > 
  > require("gamboostLSS")
  Loading required package: gamboostLSS
  Loading required package: mboost
  Loading required package: parallel
  Loading required package: stabs
  
  Attaching package: 'gamboostLSS'
  
  The following object is masked from 'package:stats':
  
      model.weights
  
  > require("gamlss")
  Loading required package: gamlss
  Warning message:
  In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
    there is no package called 'gamlss'
  > 
  > set.seed(1907)
  > n <- 5000
  > x1  <- runif(n)
  > x2 <- runif(n)
  > mu <- 2 -1*x1 - 3*x2
  > sigma <- exp(-1*x1 + 3*x2)
  > df <- exp(1 + 3*x1 + 1*x2)
  > y <- rTF(n = n, mu = mu, sigma = sigma, nu = df)
  Error in rTF(n = n, mu = mu, sigma = sigma, nu = df) : 
    could not find function "rTF"
  Execution halted
Running the tests in ‘tests/regtest-stabilization.R’ failed.
Complete output:
  > ###
  > # test functionality of stabilization
  > 
  > require("gamboostLSS")
  Loading required package: gamboostLSS
  Loading required package: mboost
  Loading required package: parallel
  Loading required package: stabs
  
  Attaching package: 'gamboostLSS'
  
  The following object is masked from 'package:stats':
  
      model.weights
  
  > 
  > ## simulate Gaussian data
  > set.seed(0804)
  > x1 <- runif(1000)
  > x2 <- runif(1000)
  > x3 <- runif(1000)
  > x4 <- runif(1000)
  > mu    <- 1.5 +1 * x1 +4 * x2
  > sigma <- exp(1 - 0.2 * x3 -0.4 * x4)
  > y <- rnorm(mean = mu, sd = sigma, n = length(mu))
  > dat <- data.frame(x1, x2, x3, x4, y)
  > 
  > ## do not use stabilization
  > m1 <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                   families=GaussianLSS(),
  +                   data=dat)
  > coef(m1)
  $mu
  (Intercept)          x1          x2 
   -1.9916597   0.2601562   3.6573948 
  attr(,"offset")
  [1] 4.075487
  
  $sigma
  (Intercept)          x1          x2          x3          x4 
   0.07184243 -0.08466051  0.14507711 -0.20507878 -0.34966371 
  attr(,"offset")
  [1] 0.8534752
  
  > 
  > ## use stabilization via options (for backwards compatibility)
  > options(gamboostLSS_stab_ngrad = TRUE)
  > m2 <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                   families=GaussianLSS(),
  +                   data=dat)
  Warning messages:
  1: In check_stabilization(stabilization) :
    Usage of 'options(gamboostLSS_stab_ngrad = TRUE)' is deprecated.
  Use argument 'stabilization' in the fitting family. See ?Families for details.
  2: In check_stabilization(stabilization) : 'stabilization' is set to "MAD"
  > coef(m2)
  $mu
  (Intercept)          x1          x2 
   -2.5558491   0.8170992   4.2184347 
  attr(,"offset")
  [1] 4.075487
  
  $sigma
  (Intercept)          x1          x2          x3          x4 
    0.1071746  -0.1188396   0.1373902  -0.2372693  -0.3712830 
  attr(,"offset")
  [1] 0.8534752
  
  > options(gamboostLSS_stab_ngrad = FALSE)
  > 
  > ## now use novel interface via families:
  > m3 <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                   families = GaussianLSS(stabilization = "MAD"),
  +                   data=dat)
  > stopifnot(all.equal(coef(m3), coef(m2)))
  > 
  > ## check if everything is handled correctly
  > GaussianLSS(stabilization = "MAD")
  $mu
  
  	 Normal distribution: mu(id link) 
  
  Loss function: -dnorm(x = y, mean = f, sd = sigma, log = TRUE) 
   
  
  $sigma
  
  	 Normal distribution: sigma (log link) 
  
  Loss function: -dnorm(x = y, mean = mu, sd = exp(f), log = TRUE) 
   
  
  attr(,"class")
  [1] "families"
  attr(,"qfun")
  function (p, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE) 
  {
      qnorm(p = p, mean = mu, sd = sigma, lower.tail = lower.tail, 
          log.p = log.p)
  }
  <bytecode: 0x226b0688>
  <environment: namespace:gamboostLSS>
  attr(,"name")
  [1] "Gaussian"
  > GaussianLSS(stabilization = "L2")
  $mu
  
  	 Normal distribution: mu(id link) 
  
  Loss function: -dnorm(x = y, mean = f, sd = sigma, log = TRUE) 
   
  
  $sigma
  
  	 Normal distribution: sigma (log link) 
  
  Loss function: -dnorm(x = y, mean = mu, sd = exp(f), log = TRUE) 
   
  
  attr(,"class")
  [1] "families"
  attr(,"qfun")
  function (p, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE) 
  {
      qnorm(p = p, mean = mu, sd = sigma, lower.tail = lower.tail, 
          log.p = log.p)
  }
  <bytecode: 0x226b0688>
  <environment: namespace:gamboostLSS>
  attr(,"name")
  [1] "Gaussian"
  > GaussianLSS(stabilization = "none")
  $mu
  
  	 Normal distribution: mu(id link) 
  
  Loss function: -dnorm(x = y, mean = f, sd = sigma, log = TRUE) 
   
  
  $sigma
  
  	 Normal distribution: sigma (log link) 
  
  Loss function: -dnorm(x = y, mean = mu, sd = exp(f), log = TRUE) 
   
  
  attr(,"class")
  [1] "families"
  attr(,"qfun")
  function (p, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE) 
  {
      qnorm(p = p, mean = mu, sd = sigma, lower.tail = lower.tail, 
          log.p = log.p)
  }
  <bytecode: 0x226b0688>
  <environment: namespace:gamboostLSS>
  attr(,"name")
  [1] "Gaussian"
  > res <- try(GaussianLSS(stabilization = "test"), silent = TRUE)
  > res
  [1] "Error in match.arg(stabilization) : \n  'arg' should be one of \"none\", \"MAD\", \"L2\"\n"
  attr(,"class")
  [1] "try-error"
  attr(,"condition")
  <simpleError in match.arg(stabilization): 'arg' should be one of "none", "MAD", "L2">
  > 
  > 
  > ############################################################
  > ## continue these checks for other families
  > dat$y <- runif(1000, min = 0.01, max = 0.99)
  > FAMILIES <- list(
  +     GaussianLSS,
  +     GammaLSS,
  +     BetaLSS,
  +     StudentTLSS)
  > for (i in 1:length(FAMILIES)) {
  +     m_none <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                           families = FAMILIES[[i]](stabilization = "none"),
  +                           data=dat)
  +     m_MAD <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                          families = FAMILIES[[i]](stabilization = "MAD"),
  +                          data=dat)
  +     m_L2 <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                          families = FAMILIES[[i]](stabilization = "L2"),
  +                          data=dat)
  +     
  +     stopifnot(tail(risk(m_none, merge = TRUE), 1) != tail(risk(m_MAD, merge = TRUE), 1))
  +     cat('Risks:\n  stabilization = "none":',
  +         tail(risk(m_none, merge = TRUE), 1),
  +         '\n  stabilization = "MAD":',
  +         tail(risk(m_MAD, merge = TRUE), 1), 
  +         '\n  stabilization = "L2":', 
  +         tail(risk(m_L2, merge = TRUE), 1), "\n")
  + }
  Risks:
    stabilization = "none": 126.3867 
    stabilization = "MAD": 126.3865 
    stabilization = "L2": 126.3866 
  Risks:
    stabilization = "none": 152.9363 
    stabilization = "MAD": 151.7991 
    stabilization = "L2": 152.3966 
  Risks:
    stabilization = "none": -16.74875 
    stabilization = "MAD": -16.85658 
    stabilization = "L2": -16.81103 
  Risks:
    stabilization = "none": 126.3869 
    stabilization = "MAD": 126.3865 
    stabilization = "L2": 126.3867 
  > 
  > ## check as.families interface for 2:4 parametric families
  > dat$y <- rnorm(1000, mean = 10, sd = 1)
  > FAMILIES <- list(
  +     "NO",
  +     "TF")
  > for (i in 1:length(FAMILIES)) {
  +     m_none <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                           families = as.families(FAMILIES[[i]], stabilization = "none"),
  +                           data=dat)
  +     m_MAD <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                          families = as.families(FAMILIES[[i]], stabilization = "MAD"),
  +                          data=dat)
  +     m_L2 <- glmboostLSS(y ~ x1 + x2 + x3 + x4,
  +                          families = as.families(FAMILIES[[i]], stabilization = "L2"),
  +                          data=dat)
  +     cat('Risks:\n  stabilization = "none":',
  +         tail(risk(m_none, merge = TRUE), 1),
  +         '\n  stabilization = "MAD":',
  +         tail(risk(m_MAD, merge = TRUE), 1), 
  +         '\n  stabilization = "L2":', 
  +         tail(risk(m_L2, merge = TRUE), 1), "\n")
  + }
  Error in as.families(FAMILIES[[i]], stabilization = "none") : 
    Please install package 'gamlss.dist' for using gamlss families.
  Calls: glmboostLSS -> mboostLSS_fit -> as.families
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ...