CRAN Package Check Results for Package BayesianMCPMod

Last updated on 2024-03-28 07:52:44 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.0 3.57 462.26 465.83 OK
r-devel-linux-x86_64-debian-gcc 1.0.0 2.37 338.97 341.34 OK
r-devel-linux-x86_64-fedora-clang 1.0.0 537.37 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.0 560.26 OK
r-devel-windows-x86_64 1.0.0 5.00 327.00 332.00 OK
r-patched-linux-x86_64 1.0.0 2.27 458.63 460.90 OK
r-release-linux-x86_64 1.0.0 2.05 463.64 465.69 OK
r-release-macos-arm64 1.0.0 138.00 OK
r-release-macos-x86_64 1.0.0 339.00 OK
r-release-windows-x86_64 1.0.0 5.00 415.00 420.00 OK
r-oldrel-macos-arm64 1.0.0 140.00 OK
r-oldrel-windows-x86_64 1.0.0 5.00 412.00 417.00 OK

Additional issues

noLD

Check Details

Version: 1.0.0
Check: tests
Result: ERROR Running ‘spelling.R’ Running ‘testthat.R’ [247s/510s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(BayesianMCPMod) > > test_check("BayesianMCPMod") Loading required package: rstan Loading required package: StanHeaders rstan version 2.32.6 (Stan version 2.32.2) For execution on a local, multicore CPU with excess RAM we recommend calling options(mc.cores = parallel::detectCores()). To avoid recompilation of unchanged Stan programs, we recommend calling rstan_options(auto_write = TRUE) For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions, change `threads_per_chain` option: rstan_options(threads_per_chain = 1) Loading required package: shiny Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Using default prior reference scale 7.06484551805801 Using default prior reference scale 7.1096879209905 Using default prior reference scale 7.1096879209905 Using default prior reference scale 7.1096879209905 $Ctr Univariate normal mixture Reference scale: 9.21011 Mixture Components: comp1 comp2 comp3 robust w 0.24699155 0.23796496 0.01504349 0.50000000 m -12.23859230 -12.26640123 -11.18259121 -12.22005552 s 1.03190075 2.36439673 5.15553875 9.30805148 $DG_1 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 $DG_2 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 $DG_3 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 $`Summary of Posterior Distributions` mean sd 2.5% 50.0% 97.5% Ctr -12.22006 6.732746 -27.5325 -12.23543 3.097944 DG_1 -12.22006 9.308051 -30.4635 -12.22006 6.023390 DG_2 -12.22006 9.308051 -30.4635 -12.22006 6.023390 DG_3 -12.22006 9.308051 -30.4635 -12.22006 6.023390 $`Maximum Difference to Control and Dose Group` max_diff DG 0.01537532 1.00000000 $`Posterior Distributions` $`Posterior Distributions`$Ctr Univariate normal mixture Reference scale: 9.21011 Mixture Components: comp1 comp2 comp3 robust w 0.24699155 0.23796496 0.01504349 0.50000000 m -12.23859230 -12.26640123 -11.18259121 -12.22005552 s 1.03190075 2.36439673 5.15553875 9.30805148 $`Posterior Distributions`$DG_1 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 $`Posterior Distributions`$DG_2 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 $`Posterior Distributions`$DG_3 Univariate normal mixture Reference scale: 9.308051 Mixture Components: comp1 w 1.000000 m -12.220056 s 9.308051 Model Coefficients linear e0 = 0.4 delta = -0.3 Dose Levels Ctr = 0 DG_1 = 2.5 Predictions, Maximum Effect, gAIC, Model Weights & Significance Ctr DG_1 mEff gAIC w 0.4 -0.3 0.8 4.0 1.0 [ FAIL 1 | WARN 0 | SKIP 0 | PASS 71 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-BMCPMod.R:259:3'): BayesMCPi function works correctly in a simple case ── result[["sign"]] (`actual`) not equal to 1 (`expected`). `actual`: 0 `expected`: 1 [ FAIL 1 | WARN 0 | SKIP 0 | PASS 71 ] Error: Test failures Execution halted Flavor: r-devel-linux-x86_64-fedora-clang