Check results for 'extraSuperpower'

using R version 4.4.1 (2024-06-14)
using platform: aarch64-apple-darwin20
R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0
running under: macOS Ventura 13.4
using session charset: UTF-8
checking for file ‘extraSuperpower/DESCRIPTION’ ... OK
this is package ‘extraSuperpower’ version ‘1.6.0’
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 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 ‘extraSuperpower’ can be installed ... [3s/3s] OK See the install log for details.
checking installed package size ... 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 ... [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 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 ... [3s/3s] OK
checking Rd files ... [0s/0s] 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 installed files from ‘inst/doc’ ... OK
checking files in ‘vignettes’ ... OK
checking examples ... [11s/13s] OK
checking for unstated dependencies in ‘tests’ ... OK
checking tests ... [112s/137s] ERROR Running ‘testthat.R’ [112s/137s] 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/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(extraSuperpower) > > test_check("extraSuperpower") Correlation matrix names assigned based on names from the mean matrix Correlation matrix names assigned based on names from the mean matrix Correlation matrix names assigned based on names from the mean matrix Simulating independent observations experiment Simulating independent observations experiment Simulating independent observations experiment Simulating independent observations experiment Simulating independent observations experiment Simulating repeated observations experiment Simulating repeated observations experiment Simulating independent observations experiment Testing power on an independent observations design experiment. Sample size per group = 9 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 11 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 13 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 15 Performing ANOVA testing on simulated data Simulating independent observations experiment Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Simulating independent observations experiment Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Simulating independent observations experiment Simulating repeated observations experiment Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 6 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 8 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 6 Testing power on an independent observations design experiment. Sample size per group = 8 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 8 Performing permutation testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 6 Testing power on an independent observations design experiment. Sample size per group = 8 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 8 Performing rank testing on simulated data Simulating independent observations experiment Testing power on an independent observations design experiment. Mean sample size per group = 6.5 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Mean sample size per group = 7.5 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Mean sample size per group = 8.5 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Mean sample size per group = 9.5 Performing ANOVA testing on simulated data Performing ANOVA testing on simulated data Performing ANOVA testing on simulated data Performing ANOVA testing on simulated data Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Sample size per group = 5 Testing power on an independent observations design experiment. Sample size per group = 5 Testing power on an independent observations design experiment. Sample size per group = 5 Testing power on an independent observations design experiment. Mean sample size per group = 7.1 Performing ANOVA testing on simulated data Testing power on an independent observations design experiment. Mean sample size per group = 7.1 Performing permutation testing on simulated data Testing power on an independent observations design experiment. Mean sample size per group = 7.1 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 15 Testing power on a repeated observations design experiment. Sample size = 15 Testing power on a repeated observations design experiment. Sample size = 15 Testing power on a repeated observations design experiment. Sample size = 5 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 15 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 15 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 5 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 15 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing rank testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing ANOVA testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing permutation testing on simulated data Testing power on a repeated observations design experiment. Sample size = 6 Testing power on a repeated observations design experiment. Sample size = 5 Testing power on a repeated observations design experiment. Sample size = 4 Testing power on a repeated observations design experiment. Sample size = 3 Performing permutation testing on simulated data [ FAIL 1 | WARN 439 | SKIP 0 | PASS 279 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-twoway_simulation_testing.R:168:3'): correct within factor is used ── res_fB[2, 2] is not strictly less than 0.5. Difference: 0.0143 [ FAIL 1 | WARN 439 | SKIP 0 | PASS 279 ] Error: Test failures Execution halted
checking for unstated dependencies in vignettes ... OK
checking package vignettes ... OK
checking re-building of vignette outputs ... [35s/63s] OK
checking PDF version of manual ... [3s/3s] OK
DONE Status: 1 ERROR
using check arguments '--no-clean-on-error '