* using log directory ‘/srv/hornik/tmp/CRAN/eDNAjoint.Rcheck’ * using R Under development (unstable) (2023-08-28 r85029) * using platform: x86_64-pc-linux-gnu * R was compiled by Debian clang version 16.0.6 (10) GNU Fortran (Debian 13.2.0-1) 13.2.0 * running under: Debian GNU/Linux trixie/sid * using session charset: UTF-8 * checking for file ‘eDNAjoint/DESCRIPTION’ ... OK * this is package ‘eDNAjoint’ version ‘0.1’ * package encoding: UTF-8 * checking CRAN incoming feasibility ... [3s/4s] NOTE Maintainer: ‘Abigail G. Keller ’ New submission Possibly misspelled words in DESCRIPTION: catchability (8:557) eDNA (8:50, 8:261, 8:437, 8:507) electrofishing (8:222) nondetection (8:276) polymerase (8:298) qPCR (8:338) Found the following (possibly) invalid file URI: URI: doi.org/10.6084/m9.figshare.15117102.v2 From: man/greencrabData.Rd * 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 serialization versions ... OK * checking whether package ‘eDNAjoint’ can be installed ... [480s/480s] OK * used C++ compiler: ‘Debian clang version 16.0.6 (11)’ * checking C++ specification ... OK Not all R platforms support C++17 * checking package directory ... OK * checking for future file timestamps ... 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 R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... [1s/1s] OK * checking whether the package can be loaded with stated dependencies ... [1s/1s] OK * checking whether the package can be unloaded cleanly ... [1s/1s] OK * checking whether the namespace can be loaded with stated dependencies ... [1s/1s] OK * checking whether the namespace can be unloaded cleanly ... [1s/1s] OK * checking loading without being on the library search path ... [1s/1s] 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 ... [8s/8s] OK * checking Rd files ... [0s/0s] 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 ... [0s/0s] OK * checking LazyData ... OK * checking data for ASCII and uncompressed saves ... OK * checking line endings in shell scripts ... 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 $(LAPACK_LIBS) ... OK * checking use of PKG_*FLAGS in Makefiles ... OK * checking use of SHLIB_OPENMP_*FLAGS in Makefiles ... OK * checking pragmas in C/C++ headers and code ... OK * checking compilation flags used ... OK * checking compiled code ... OK * checking installed files from ‘inst/doc’ ... OK * checking files in ‘vignettes’ ... OK * checking examples ... [0m/30m] ERROR Running examples in ‘eDNAjoint-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: traditionalModel > ### Title: Specify and fit model using count data from traditional > ### (non-eDNA) surveys > ### Aliases: traditionalModel > > ### ** Examples > > data(greencrabData) > > # Examine data in list > # This function uses only traditional survey count data and optionally the count type data > names(greencrabData) [1] "qPCR.N" "qPCR.K" "count" "count.type" > > # Note that the surveyed sites (rows) should match in the data > dim(greencrabData$count)[1] [1] 20 > dim(greencrabData$count.type)[1] [1] 20 > > # Fit a model without estimating a catchability coefficient for traditional survey gear types. > # This model assumes all traditional survey methods have the same catchability. > # Count data is modeled using a poisson distribution. > fit.no.q = traditionalModel(data=greencrabData, family='poisson', q=FALSE) SAMPLING FOR MODEL 'traditional_pois' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 7.4e-05 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.74 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 1: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 1: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 1: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 1: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 1: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 1: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 1: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 1: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 1: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 1: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 1: Iteration: 3000 / 3000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0.617 seconds (Warm-up) Chain 1: 1.692 seconds (Sampling) Chain 1: 2.309 seconds (Total) Chain 1: SAMPLING FOR MODEL 'traditional_pois' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 7.1e-05 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.71 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 2: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 2: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 2: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 2: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 2: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 2: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 2: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 2: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 2: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 2: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 2: Iteration: 3000 / 3000 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 0.665 seconds (Warm-up) Chain 2: 1.848 seconds (Sampling) Chain 2: 2.513 seconds (Total) Chain 2: SAMPLING FOR MODEL 'traditional_pois' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 6.9e-05 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.69 seconds. Chain 3: Adjust your expectations accordingly! Chain 3: Chain 3: Chain 3: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 3: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 3: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 3: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 3: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 3: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 3: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 3: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 3: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 3: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 3: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 3: Iteration: 3000 / 3000 [100%] (Sampling) Chain 3: Chain 3: Elapsed Time: 0.616 seconds (Warm-up) Chain 3: 1.418 seconds (Sampling) Chain 3: 2.034 seconds (Total) Chain 3: SAMPLING FOR MODEL 'traditional_pois' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 6.9e-05 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.69 seconds. Chain 4: Adjust your expectations accordingly! Chain 4: Chain 4: Chain 4: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 4: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 4: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 4: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 4: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 4: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 4: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 4: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 4: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 4: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 4: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 4: Iteration: 3000 / 3000 [100%] (Sampling) Chain 4: Chain 4: Elapsed Time: 0.651 seconds (Warm-up) Chain 4: 1.629 seconds (Sampling) Chain 4: 2.28 seconds (Total) Chain 4: > > > # Fit a model estimating a catchability coefficient for traditional survey gear types. > # This model does not assume all traditional survey methods have the same catchability. > # Gear type 1 is used as the reference gear type. > # The catchability of all other gear types are scaled relative to the catchability of type 1. > # Count data is modeled using a negative binomial distribution. > fit.q = traditionalModel(data=greencrabData, family='negbin', q=TRUE, q_ref=1) SAMPLING FOR MODEL 'traditional_catchability_negbin' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000253 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.53 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 1: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 1: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 1: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 1: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 1: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 1: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 1: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 1: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 1: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 1: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 1: Iteration: 3000 / 3000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.707 seconds (Warm-up) Chain 1: 6.736 seconds (Sampling) Chain 1: 9.443 seconds (Total) Chain 1: SAMPLING FOR MODEL 'traditional_catchability_negbin' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 0.000263 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 2.63 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 2: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 2: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 2: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 2: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 2: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 2: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 2: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 2: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 2: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 2: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 2: Iteration: 3000 / 3000 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 2.657 seconds (Warm-up) Chain 2: 6.677 seconds (Sampling) Chain 2: 9.334 seconds (Total) Chain 2: SAMPLING FOR MODEL 'traditional_catchability_negbin' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 0.000257 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 2.57 seconds. Chain 3: Adjust your expectations accordingly! Chain 3: Chain 3: Chain 3: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 3: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 3: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 3: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 3: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 3: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 3: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 3: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 3: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 3: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 3: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 3: Iteration: 3000 / 3000 [100%] (Sampling) Chain 3: Chain 3: Elapsed Time: 2.637 seconds (Warm-up) Chain 3: 5.485 seconds (Sampling) Chain 3: 8.122 seconds (Total) Chain 3: SAMPLING FOR MODEL 'traditional_catchability_negbin' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 0.000287 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 2.87 seconds. Chain 4: Adjust your expectations accordingly! Chain 4: Chain 4: Chain 4: Iteration: 1 / 3000 [ 0%] (Warmup) Chain 4: Iteration: 300 / 3000 [ 10%] (Warmup) Chain 4: Iteration: 501 / 3000 [ 16%] (Sampling) Chain 4: Iteration: 800 / 3000 [ 26%] (Sampling) Chain 4: Iteration: 1100 / 3000 [ 36%] (Sampling) Chain 4: Iteration: 1400 / 3000 [ 46%] (Sampling) Chain 4: Iteration: 1700 / 3000 [ 56%] (Sampling) Chain 4: Iteration: 2000 / 3000 [ 66%] (Sampling) Chain 4: Iteration: 2300 / 3000 [ 76%] (Sampling) Chain 4: Iteration: 2600 / 3000 [ 86%] (Sampling) Chain 4: Iteration: 2900 / 3000 [ 96%] (Sampling) Chain 4: Iteration: 3000 / 3000 [100%] (Sampling) Chain 4: Chain 4: Elapsed Time: 2.717 seconds (Warm-up) Chain 4: 5.261 seconds (Sampling) Chain 4: 7.978 seconds (Total) Chain 4: > > > > > base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv") > base::cat("traditionalModel", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t") > ### *