R Under development (unstable) (2024-07-24 r86924 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # 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(smdi) > > test_check("smdi") Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. Windows does not support parallelization based on forking. will be automatically set to 1. covariate hotteling_p 1 x 0.667 2 y 0.667 covariate hotteling_p 1 x 0.667 2 y 0.667 Windows does not support parallelization based on forking. will be automatically set to 1. not specified. Using 'binomial(link = 'logit')' as default. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. # A tibble: 1 x 2 covariate rf_auc * 1 var2 0.750 # A tibble: 1 x 2 covariate rf_auc * 1 var2 0.750 Windows does not support parallelization based on forking. will be set to 1. Important note: AUC for predicting covariate var3 is very high (>0.9). Predictor with highest importance: var1.Predictor with highest importance: var2_NA.Predictor with highest importance: var4_NA. Check for potentially underlying monotone missing data pattern. Important note: AUC for predicting covariate var4 is very high (>0.9). Predictor with highest importance: var1.Predictor with highest importance: var2_NA.Predictor with highest importance: var3_NA. Check for potentially underlying monotone missing data pattern. # A tibble: 3 x 2 covariate rf_auc * 1 var2 0.750 2 var3 1.000 3 var4 1.000 # A tibble: 3 x 2 covariate rf_auc * 1 var2 0.750 2 var3 1.000 3 var4 1.000 Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. Important note: AUC for predicting covariate var3 is very high (>0.9). Predictor with highest importance: var1.Predictor with highest importance: var2_NA.Predictor with highest importance: var4_NA. Check for potentially underlying monotone missing data pattern. Important note: AUC for predicting covariate var4 is very high (>0.9). Predictor with highest importance: var1.Predictor with highest importance: var2_NA.Predictor with highest importance: var3_NA. Check for potentially underlying monotone missing data pattern. Windows does not support parallelization based on forking. will be set to 1. AUC for predicting covariate var1 is very high (>0.9). Predictor with highest importance: var2_NA. Check for potentially underlying monotone missing data pattern. Important note: AUC for predicting covariate var2 is very high (>0.9). Predictor with highest importance: var1_NA. Check for potentially underlying monotone missing data pattern. Windows does not support parallelization based on forking. will be set to 1. Windows does not support parallelization based on forking. will be set to 1. Loading required package: ggplot2 Loading required package: lattice Attaching package: 'caret' The following object is masked from 'package:survival': cluster [ FAIL 0 | WARN 6 | SKIP 2 | PASS 188 ] ══ Skipped tests (2) ═══════════════════════════════════════════════════════════ • On CRAN (2): 'test-smdi_vis.R:10:3', 'test-smdi_vis.R:17:3' [ FAIL 0 | WARN 6 | SKIP 2 | PASS 188 ] > > proc.time() user system elapsed 11.65 1.31 12.95