CRAN Package Check Results for Package scoringTools

Last updated on 2021-05-18 17:48:25 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.2 4.83 365.89 370.72 OK
r-devel-linux-x86_64-debian-gcc 0.1.2 3.13 251.87 255.00 OK
r-devel-linux-x86_64-fedora-clang 0.1.2 546.03 OK
r-devel-linux-x86_64-fedora-gcc 0.1.2 492.19 OK
r-devel-windows-ix86+x86_64 0.1.2 14.00 266.00 280.00 OK
r-devel-windows-x86_64-gcc10-UCRT 0.1.2 OK
r-patched-linux-x86_64 0.1.2 5.27 404.93 410.20 OK
r-patched-solaris-x86 0.1.2 489.90 ERROR
r-release-linux-x86_64 0.1.2 4.40 349.80 354.20 OK
r-release-macos-x86_64 0.1.2 OK
r-release-windows-ix86+x86_64 0.1.2 9.00 255.00 264.00 OK
r-oldrel-macos-x86_64 0.1.2 OK
r-oldrel-windows-ix86+x86_64 0.1.2 5.00 422.00 427.00 OK

Check Details

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘testthat.R’ [321s/492s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(scoringTools)
     >
     > test_check("scoringTools")
     Generalized Linear Model of class 'speedglm':
    
     Call: speedglm::speedglm(formula = labels ~ ., data = df_augmente[, -which(names(df_augmente) %in% c("poidsfinal", "classe_SCORE"))][!df_augmente$poidsfinal == 0, ], family = stats::binomial(link = "logit"), weights = df_augmente$poidsfinal[!df_augmente$poidsfinal == 0])
    
     Coefficients:
     (Intercept) x.1 x.2
     0.636 1.168 -2.643
    
     Generalized Linear Model of class 'speedglm':
    
     Call: speedglm::speedglm(formula = stats::formula("labels ~ ."), data = Filter(function(x) (length(unique(x)) > 1), cbind(data.frame(sapply(disc$Disc.data, as.factor), stringsAsFactors = TRUE), data_train[, sapply(data_train, is.factor), drop = FALSE])), family = stats::binomial(link = "logit"), weights = NULL, fitted = TRUE)
    
     Coefficients:
     (Intercept) X12 X13 X22
     -0.290 2.484 -0.243 -2.393
    
     Generalized Linear Model of class 'speedglm':
    
     Call: speedglm::speedglm(formula = stats::formula("labels ~ ."), data = Filter(function(x) (length(unique(x)) > 1), cbind(data.frame(sapply(disc$Disc.data, as.factor), stringsAsFactors = TRUE), data_train[, sapply(data_train, is.factor), drop = FALSE])), family = stats::binomial(link = "logit"), weights = NULL, fitted = TRUE)
    
     Coefficients:
     (Intercept) X12 X13 X22
     -0.290 2.484 -0.243 -2.393
    
     ══ Failed tests ════════════════════════════════════════════════════════════════
     ── Error (test-topdown.R:54:9): topdown method works with speedglm and glm on dataframes with additional factors ──
     Error: system is computationally singular: reciprocal condition number = 7.40145e-17
     Backtrace:
     █
     1. └─scoringTools::topdown_iter(...) test-topdown.R:54:8
     2. └─scoringTools:::fit_disc(disc[[i]], data_train, type = "speedglm")
     3. └─speedglm::speedglm(...)
     4. └─speedglm::speedglm.wfit(...)
     5. ├─base::solve(XTX, XTz, tol = tol.solve)
     6. ├─base::solve(XTX, XTz, tol = tol.solve)
     7. └─base::solve.default(XTX, XTz, tol = tol.solve)
    
     [ FAIL 1 | WARN 90 | SKIP 0 | PASS 945 ]
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86