* using log directory 'd:/Rcompile/CRANpkg/local/4.3/epigrowthfit.Rcheck'
* using R version 4.3.3 (2024-02-29 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
    gcc.exe (GCC) 12.3.0
    GNU Fortran (GCC) 12.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* checking for file 'epigrowthfit/DESCRIPTION' ... OK
* this is package 'epigrowthfit' version '0.15.3'
* package encoding: UTF-8
* 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 hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'epigrowthfit' can be installed ... OK
* used C++ compiler: 'g++.exe (GCC) 12.3.0'
* checking installed package size ... NOTE
  installed size is 14.2Mb
  sub-directories of 1Mb or more:
    libs  13.7Mb
* 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 R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... [2s] OK
* checking whether the package can be loaded with stated dependencies ... [2s] OK
* checking whether the package can be unloaded cleanly ... [2s] OK
* checking whether the namespace can be loaded with stated dependencies ... [2s] OK
* checking whether the namespace can be unloaded cleanly ... [2s] OK
* checking loading without being on the library search path ... [2s] OK
* checking startup messages can be suppressed ... [2s] 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 ... [18s] OK
* checking Rd files ... [1s] OK
* 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 ... [0s] OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking pragmas in C/C++ headers and code ... OK
* checking compiled code ... OK
* checking examples ... [43s] OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ... [381s] ERROR
  Running 'coef.R' [7s]
  Running 'confint.R' [75s]
  Running 'datetime.R' [2s]
  Running 'egf.R' [7s]
  Running 'egf_enum.R' [2s]
  Running 'egf_eval.R' [2s]
  Running 'egf_examples_day_of_week.R' [3s]
  Running 'egf_examples_excess.R' [2s]
  Running 'egf_examples_fixed.R' [3s]
  Running 'egf_examples_random.R' [39s]
  Running 'egf_link.R' [2s]
  Running 'egf_misc.R' [8s]
  Running 'egf_options.R' [2s]
  Running 'egf_utils.R' [9s]
  Running 'epidemic.R' [2s]
  Running 'extract.R' [7s]
  Running 'fitted.R' [7s]
  Running 'gi.R' [2s]
  Running 'include.R' [130s]
  Running 'language.R' [2s]
  Running 'prior.R' [2s]
  Running 'profile.R' [48s]
  Running 'summary.R' [7s]
  Running 'utils.R' [2s]
  Running 'validity.R' [2s]
  Running 'zzz.R' [2s]
Running the tests in 'tests/egf_examples_random.R' failed.
Complete output:
  > library(epigrowthfit)
  > options(warn = 2L, error = if (interactive()) recover, egf.cores = 2L)
  > 
  > 
  > ## exponential #########################################################
  > 
  > r <- log(2) / 20
  > c0 <- 100
  > s <- 0.2
  > 
  > mu <- log(c(r, c0))
  > Sigma <- diag(rep.int(s^2, length(mu)))
  > 
  > zz <- simulate(egf_model(curve = "exponential", family = "pois"),
  +                nsim = 20L,
  +                seed = 775494L,
  +                mu = mu,
  +                Sigma = Sigma,
  +                cstart = 10)
  > mm <- egf(zz,
  +           formula_priors = list(Sigma ~ LKJ(eta = 2)))
  > 
  > p1 <- as.list(coef(zz))
  > p2 <- as.list(coef(mm))
  > 
  > stopifnot(exprs = {
  + 	max(abs(mm[["gradient"]])) < 5e-05
  + 	all.equal(p1[["beta"]], p2[["beta"]], tolerance = 5e-02)
  + 	all.equal(theta2cov(p1[["theta"]]), theta2cov(p2[["theta"]]), tolerance = 5e-02)
  + })
  > 
  > 
  > ## subexponential ######################################################
  > 
  > alpha <- log(2) / 20
  > c0 <- 100
  > p <- 0.95
  > s <- 0.2
  > 
  > mu <- c(log(alpha), log(c0), qlogis(p))
  > Sigma <- diag(rep.int(s^2, length(mu)))
  > 
  > zz <- simulate(egf_model(curve = "subexponential", family = "pois"),
  +                nsim = 20L,
  +                seed = 653927L,
  +                mu = mu,
  +                Sigma = Sigma,
  +                cstart = 10)
  > mm <- egf(zz,
  +           formula_priors = list(beta[3L] ~ Normal(mu = qlogis(p), sigma = 0.05),
  +                                 theta[3L] ~ Normal(mu = log(s), sigma = 0.25),
  +                                 Sigma ~ LKJ(eta = 2)))
  > 
  > p1 <- as.list(coef(zz))
  > p2 <- as.list(coef(mm))
  > 
  > stopifnot(exprs = {
  + 	max(abs(mm[["gradient"]])) < 5e-04
  + 	all.equal(p1[["beta"]], p2[["beta"]], tolerance = 5e-02)
  + 	all.equal(theta2cov(p1[["theta"]]), theta2cov(p2[["theta"]]), tolerance = 2e-02)
  + })
  > 
  > 
  > ## gompertz ############################################################
  > 
  > alpha <- log(2) / 20
  > tinfl <- 100
  > K <- 25000
  > s <- 0.2
  > 
  > mu <- log(c(alpha, tinfl, K))
  > Sigma <- diag(rep.int(s^2, length(mu)))
  > 
  > zz <- simulate(egf_model(curve = "gompertz", family = "pois"),
  +                nsim = 20L,
  +                seed = 685399L,
  +                mu = mu,
  +                Sigma = Sigma,
  +                cstart = 10)
  > oo <- options(warn = 1L) # FIXME: diagnose NA/NaN function evaluation
  > mm <- egf(zz,
  +           formula_priors = list(Sigma ~ LKJ(eta = 2)))
  > options(oo)
  > 
  > p1 <- as.list(coef(zz))
  > p2 <- as.list(coef(mm))
  > 
  > stopifnot(exprs = {
  + 	max(abs(mm[["gradient"]])) < 5e-04
  + 	all.equal(p1[["beta"]], p2[["beta"]], tolerance = 5e-02)
  + 	all.equal(theta2cov(p1[["theta"]]), theta2cov(p2[["theta"]]), tolerance = 2e-02)
  + })
  Error: max(abs(mm[["gradient"]])) < 5e-04 is not TRUE
  Execution halted
* checking PDF version of manual ... [20s] OK
* checking HTML version of manual ... [10s] OK
* DONE
Status: 1 ERROR, 1 NOTE