* using log directory ‘/data/localhost/ripley/R/packages/tests-Suggests/tidyfit.Rcheck’
* using R Under development (unstable) (2026-07-14 r90255)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (GCC) 16.1.1 20260515 (Red Hat 16.1.1-2)
    GNU Fortran (GCC) 16.1.1 20260515 (Red Hat 16.1.1-2)
* running under: Fedora Linux 44 (Server Edition)
* using session charset: UTF-8
* current time: 2026-07-15 06:03:18 UTC
* using option ‘--no-stop-on-test-error’
* checking for file ‘tidyfit/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘tidyfit’ version ‘0.7.4’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Package suggested but not available for checking: ‘CORElearn’
* 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 ‘tidyfit’ can be installed ... [13s/14s] 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 ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... 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 ... [13s/14s] OK
* checking Rd files ... 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 ... OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘tidyfit-Ex.R’ failed
The error most likely occurred in:

> ### Name: classify
> ### Title: Classification on tidy data
> ### Aliases: classify
> 
> ### ** Examples
> 
> data <- tidyfit::Factor_Industry_Returns
> data <- dplyr::mutate(data, Return = ifelse(Return > 0, 1, 0))
> fit <- classify(data, Return ~ ., m("lasso", lambda = c(0.001, 0.1)), .mask = c("Date", "Industry"))
Error in m("lasso", lambda = c(0.001, 0.1)) : 
  Package 'glmnet' is required for method 'lasso'. Run install.packages('glmnet').
Calls: classify -> m
Execution halted
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 ERROR
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(tidyfit)
  > 
  > test_check("tidyfit")
  
  Attaching package: 'dplyr'
  
  The following object is masked from 'package:tidyfit':
  
      explain
  
  The following objects are masked from 'package:stats':
  
      filter, lag
  
  The following objects are masked from 'package:base':
  
      intersect, setdiff, setequal, union
  
  Saving _problems/test-adalasso-8.R
  Saving _problems/test-adalasso-22.R
  Saving _problems/test-adalasso-35.R
  Saving _problems/test-bayes-8.R
  Saving _problems/test-bayes-22.R
  Saving _problems/test-blasso-8.R
  Saving _problems/test-bma-8.R
  Saving _problems/test-boost-8.R
  Saving _problems/test-boost-23.R
  Saving _problems/test-bridge-8.R
  Saving _problems/test-enet-8.R
  Saving _problems/test-enet-22.R
  Saving _problems/test-enet-35.R
  Saving _problems/test-gets-8.R
  Saving _problems/test-glmm-5.R
  Saving _problems/test-glmm-19.R
  Saving _problems/test-group_lasso-8.R
  Saving _problems/test-group_lasso-22.R
  Saving _problems/test-hfr-8.R
  Saving _problems/test-lasso-8.R
  Saving _problems/test-lasso-22.R
  Saving _problems/test-lasso-35.R
  Saving _problems/test-pcr-8.R
  Saving _problems/test-plsr-8.R
  Saving _problems/test-quantile-8.R
  Saving _problems/test-quantile_rf-6.R
  Saving _problems/test-rf-8.R
  Saving _problems/test-rf-22.R
  Saving _problems/test-ridge-8.R
  Saving _problems/test-ridge-22.R
  Saving _problems/test-ridge-35.R
  Saving _problems/test-spikeslab-8.R
  Saving _problems/test-spikeslab-22.R
  Saving _problems/test-svm-8.R
  Saving _problems/test-svm-22.R
  Saving _problems/test-svm-34.R
  [ FAIL 36 | WARN 0 | SKIP 0 | PASS 22 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-adalasso.R:8:3'): adalasso regression works ────────────────────
  Error in `m("adalasso", medv ~ ., df_reg, lambda = c(0.1))`: Package 'glmnet' is required for method 'adalasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. └─tidyfit::m("adalasso", medv ~ ., df_reg, lambda = c(0.1)) at test-adalasso.R:8:3
  ── Error ('test-adalasso.R:22:3'): adalasso classification works ───────────────
  Error in `m("adalasso", lambda = c(0.1))`: Package 'glmnet' is required for method 'adalasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls3, Species ~ ., m("adalasso", lambda = c(0.1))) at test-adalasso.R:22:3
   2. └─tidyfit::m("adalasso", lambda = c(0.1))
  ── Error ('test-adalasso.R:35:3'): adalasso classification (2class) works ──────
  Error in `m("adalasso", lambda = c(0.01))`: Package 'glmnet' is required for method 'adalasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("adalasso", lambda = c(0.01))) at test-adalasso.R:35:3
   2. └─tidyfit::m("adalasso", lambda = c(0.01))
  ── Error ('test-bayes.R:8:3'): bayes regression works ──────────────────────────
  Error in `m("bayes", medv ~ ., df_reg)`: Package 'arm' is required for method 'bayes'. Run install.packages('arm').
  Backtrace:
      ▆
   1. └─tidyfit::m("bayes", medv ~ ., df_reg) at test-bayes.R:8:3
  ── Error ('test-bayes.R:22:3'): bayes classification works ─────────────────────
  Error in `m("bayes")`: Package 'arm' is required for method 'bayes'. Run install.packages('arm').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("bayes")) at test-bayes.R:22:3
   2. └─tidyfit::m("bayes")
  ── Error ('test-blasso.R:8:3'): blasso regression works ────────────────────────
  Error in `m("blasso", medv ~ ., df_reg)`: Package 'monomvn' is required for method 'blasso'. Run install.packages('monomvn').
  Backtrace:
      ▆
   1. └─tidyfit::m("blasso", medv ~ ., df_reg) at test-blasso.R:8:3
  ── Error ('test-bma.R:8:3'): bma regression works ──────────────────────────────
  Error in `m("bma", medv ~ ., df_reg)`: Package 'BMS' is required for method 'bma'. Run install.packages('BMS').
  Backtrace:
      ▆
   1. └─tidyfit::m("bma", medv ~ ., df_reg) at test-bma.R:8:3
  ── Error ('test-boost.R:8:3'): boost regression works ──────────────────────────
  Error in `m("boost", medv ~ ., df_reg, mstop = 100, nu = 0.1)`: Package 'mboost' is required for method 'boost'. Run install.packages('mboost').
  Backtrace:
      ▆
   1. └─tidyfit::m("boost", medv ~ ., df_reg, mstop = 100, nu = 0.1) at test-boost.R:8:3
  ── Error ('test-boost.R:23:3'): bayes classification works ─────────────────────
  Error in `m("boost", mstop = 100, nu = 0.1)`: Package 'mboost' is required for method 'boost'. Run install.packages('mboost').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(...) at test-boost.R:23:3
   2. └─tidyfit::m("boost", mstop = 100, nu = 0.1)
  ── Error ('test-bridge.R:8:3'): bridge regression works ────────────────────────
  Error in `m("bridge", medv ~ ., df_reg)`: Package 'monomvn' is required for method 'bridge'. Run install.packages('monomvn').
  Backtrace:
      ▆
   1. └─tidyfit::m("bridge", medv ~ ., df_reg) at test-bridge.R:8:3
  ── Error ('test-enet.R:8:3'): enet regression works ────────────────────────────
  Error in `m("enet", medv ~ ., df_reg, lambda = c(0.1), alpha = 0.1)`: Package 'glmnet' is required for method 'enet'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. └─tidyfit::m("enet", medv ~ ., df_reg, lambda = c(0.1), alpha = 0.1) at test-enet.R:8:3
  ── Error ('test-enet.R:22:3'): enet classification works ───────────────────────
  Error in `m("enet", lambda = c(0.1), alpha = 0.1)`: Package 'glmnet' is required for method 'enet'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(...) at test-enet.R:22:3
   2. └─tidyfit::m("enet", lambda = c(0.1), alpha = 0.1)
  ── Error ('test-enet.R:35:3'): enet classification (2class) works ──────────────
  Error in `m("enet", lambda = c(0.01), alpha = 0.1)`: Package 'glmnet' is required for method 'enet'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(...) at test-enet.R:35:3
   2. └─tidyfit::m("enet", lambda = c(0.01), alpha = 0.1)
  ── Error ('test-gets.R:8:3'): gets regression works ────────────────────────────
  Error in `m("gets", medv ~ ., df_reg)`: Package 'gets' is required for method 'gets'. Run install.packages('gets').
  Backtrace:
      ▆
   1. └─tidyfit::m("gets", medv ~ ., df_reg) at test-gets.R:8:3
  ── Error ('test-glmm.R:5:3'): glmm regression works ────────────────────────────
  Error in `m("glmm", Return ~ `Mkt-RF` + `Mkt-RF` | Industry, df_reg)`: Package 'lme4' is required for method 'glmm'. Run install.packages('lme4').
  Backtrace:
      ▆
   1. └─tidyfit::m("glmm", Return ~ `Mkt-RF` + `Mkt-RF` | Industry, df_reg) at test-glmm.R:5:3
  ── Error ('test-glmm.R:19:3'): glm classification works ────────────────────────
  Error in `m("glmm")`: Package 'lme4' is required for method 'glmm'. Run install.packages('lme4').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_reg, Return ~ CMA + CMA | Industry, m("glmm")) at test-glmm.R:19:3
   2. └─tidyfit::m("glmm")
  ── Error ('test-group_lasso.R:8:3'): group_lasso regression works ──────────────
  Error in `m("group_lasso", medv ~ ., df_reg, lambda = c(0.1))`: Package 'gglasso' is required for method 'group_lasso'. Run install.packages('gglasso').
  Backtrace:
      ▆
   1. └─tidyfit::m("group_lasso", medv ~ ., df_reg, lambda = c(0.1)) at test-group_lasso.R:8:3
  ── Error ('test-group_lasso.R:22:3'): group_lasso classification (2class) works ──
  Error in `m("group_lasso", lambda = c(0.01))`: Package 'gglasso' is required for method 'group_lasso'. Run install.packages('gglasso').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("group_lasso", lambda = c(0.01))) at test-group_lasso.R:22:3
   2. └─tidyfit::m("group_lasso", lambda = c(0.01))
  ── Error ('test-hfr.R:8:3'): hfr regression works ──────────────────────────────
  Error in `m("hfr", medv ~ ., df_reg, kappa = 0.4)`: Package 'hfr' is required for method 'hfr'. Run install.packages('hfr').
  Backtrace:
      ▆
   1. └─tidyfit::m("hfr", medv ~ ., df_reg, kappa = 0.4) at test-hfr.R:8:3
  ── Error ('test-lasso.R:8:3'): lasso regression works ──────────────────────────
  Error in `m("lasso", medv ~ ., df_reg, lambda = c(0.1))`: Package 'glmnet' is required for method 'lasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. └─tidyfit::m("lasso", medv ~ ., df_reg, lambda = c(0.1)) at test-lasso.R:8:3
  ── Error ('test-lasso.R:22:3'): lasso classification works ─────────────────────
  Error in `m("lasso", lambda = c(0.1))`: Package 'glmnet' is required for method 'lasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls3, Species ~ ., m("lasso", lambda = c(0.1))) at test-lasso.R:22:3
   2. └─tidyfit::m("lasso", lambda = c(0.1))
  ── Error ('test-lasso.R:35:3'): lasso classification (2class) works ────────────
  Error in `m("lasso", lambda = c(0.01))`: Package 'glmnet' is required for method 'lasso'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("lasso", lambda = c(0.01))) at test-lasso.R:35:3
   2. └─tidyfit::m("lasso", lambda = c(0.01))
  ── Error ('test-pcr.R:8:3'): pcr regression works ──────────────────────────────
  Error in `m("pcr", medv ~ ., df_reg, ncomp_pct = 0.4)`: Package 'pls' is required for method 'pcr'. Run install.packages('pls').
  Backtrace:
      ▆
   1. └─tidyfit::m("pcr", medv ~ ., df_reg, ncomp_pct = 0.4) at test-pcr.R:8:3
  ── Error ('test-plsr.R:8:3'): plsr regression works ────────────────────────────
  Error in `m("plsr", medv ~ ., df_reg, ncomp_pct = 0.4)`: Package 'pls' is required for method 'plsr'. Run install.packages('pls').
  Backtrace:
      ▆
   1. └─tidyfit::m("plsr", medv ~ ., df_reg, ncomp_pct = 0.4) at test-plsr.R:8:3
  ── Error ('test-quantile.R:8:3'): quantile regression works ────────────────────
  Error in `m("quantile", medv ~ ., df_reg, tau = 0.4)`: Package 'quantreg' is required for method 'quantile'. Run install.packages('quantreg').
  Backtrace:
      ▆
   1. └─tidyfit::m("quantile", medv ~ ., df_reg, tau = 0.4) at test-quantile.R:8:3
  ── Error ('test-quantile_rf.R:6:3'): quantile rf regression works ──────────────
  Error in `m("quantile_rf", medv ~ ., df_reg, tau = 0.4)`: Package 'quantregForest' is required for method 'quantile_rf'. Run install.packages('quantregForest').
  Backtrace:
      ▆
   1. └─tidyfit::m("quantile_rf", medv ~ ., df_reg, tau = 0.4) at test-quantile_rf.R:6:3
  ── Error ('test-rf.R:8:3'): rf regression works ────────────────────────────────
  Error in `m("rf", medv ~ ., df_reg)`: Package 'randomForest' is required for method 'rf'. Run install.packages('randomForest').
  Backtrace:
      ▆
   1. └─tidyfit::m("rf", medv ~ ., df_reg) at test-rf.R:8:3
  ── Error ('test-rf.R:22:3'): rf classification works ───────────────────────────
  Error in `m("rf")`: Package 'randomForest' is required for method 'rf'. Run install.packages('randomForest').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls3, Species ~ ., m("rf")) at test-rf.R:22:3
   2. └─tidyfit::m("rf")
  ── Error ('test-ridge.R:8:3'): ridge regression works ──────────────────────────
  Error in `m("ridge", medv ~ ., df_reg, lambda = c(0.1))`: Package 'glmnet' is required for method 'ridge'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. └─tidyfit::m("ridge", medv ~ ., df_reg, lambda = c(0.1)) at test-ridge.R:8:3
  ── Error ('test-ridge.R:22:3'): ridge classification works ─────────────────────
  Error in `m("ridge", lambda = c(0.1))`: Package 'glmnet' is required for method 'ridge'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls3, Species ~ ., m("ridge", lambda = c(0.1))) at test-ridge.R:22:3
   2. └─tidyfit::m("ridge", lambda = c(0.1))
  ── Error ('test-ridge.R:35:3'): ridge classification (2class) works ────────────
  Error in `m("ridge", lambda = c(0.01))`: Package 'glmnet' is required for method 'ridge'. Run install.packages('glmnet').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("ridge", lambda = c(0.01))) at test-ridge.R:35:3
   2. └─tidyfit::m("ridge", lambda = c(0.01))
  ── Error ('test-spikeslab.R:8:3'): spikeslab regression works ──────────────────
  Error in `m("spikeslab", medv ~ ., df_reg)`: Package 'BoomSpikeSlab' is required for method 'spikeslab'. Run install.packages('BoomSpikeSlab').
  Backtrace:
      ▆
   1. └─tidyfit::m("spikeslab", medv ~ ., df_reg) at test-spikeslab.R:8:3
  ── Error ('test-spikeslab.R:22:3'): spikeslab classification works ─────────────
  Error in `m("spikeslab")`: Package 'BoomSpikeSlab' is required for method 'spikeslab'. Run install.packages('BoomSpikeSlab').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("spikeslab")) at test-spikeslab.R:22:3
   2. └─tidyfit::m("spikeslab")
  ── Error ('test-svm.R:8:3'): svm regression works ──────────────────────────────
  Error in `m("svm", medv ~ ., df_reg, cost = 1)`: Package 'e1071' is required for method 'svm'. Run install.packages('e1071').
  Backtrace:
      ▆
   1. └─tidyfit::m("svm", medv ~ ., df_reg, cost = 1) at test-svm.R:8:3
  ── Error ('test-svm.R:22:3'): svm classification works ─────────────────────────
  Error in `m("svm", cost = c(1))`: Package 'e1071' is required for method 'svm'. Run install.packages('e1071').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls3, Species ~ ., m("svm", cost = c(1))) at test-svm.R:22:3
   2. └─tidyfit::m("svm", cost = c(1))
  ── Error ('test-svm.R:34:3'): svm classification (2class) works ────────────────
  Error in `m("svm", cost = c(1))`: Package 'e1071' is required for method 'svm'. Run install.packages('e1071').
  Backtrace:
      ▆
   1. ├─tidyfit::classify(df_cls2, Species ~ ., m("svm", cost = c(1))) at test-svm.R:34:3
   2. └─tidyfit::m("svm", cost = c(1))
  
  [ FAIL 36 | WARN 0 | SKIP 0 | PASS 22 ]
  Error:
  ! Test failures.
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* checking HTML version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* DONE

Status: 2 ERRORs
See
  ‘/data/localhost/ripley/R/packages/tests-Suggests/tidyfit.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 1:23.97, 70.26 + 6.78