CRAN Package Check Results for Package tidyfit

Last updated on 2025-12-06 00:49:03 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.7.4 20.99 229.80 250.79 OK
r-devel-linux-x86_64-debian-gcc 0.7.4 12.72 56.16 68.88 ERROR
r-devel-linux-x86_64-fedora-clang 0.7.4 118.00 291.28 409.28 OK
r-devel-linux-x86_64-fedora-gcc 0.7.4 67.00 449.65 516.65 OK
r-devel-windows-x86_64 0.7.4 20.00 233.00 253.00 OK
r-patched-linux-x86_64 0.7.4 18.18 211.07 229.25 OK
r-release-linux-x86_64 0.7.4 18.84 212.35 231.19 OK
r-release-macos-arm64 0.7.4 OK
r-release-macos-x86_64 0.7.4 22.00 257.00 279.00 OK
r-release-windows-x86_64 0.7.4 21.00 232.00 253.00 OK
r-oldrel-macos-arm64 0.7.4 OK
r-oldrel-macos-x86_64 0.7.4 15.00 347.00 362.00 OK
r-oldrel-windows-x86_64 0.7.4 30.00 311.00 341.00 OK

Check Details

Version: 0.7.4
Check: package dependencies
Result: WARN Cannot process vignettes Packages suggested but not available for checking: 'arm', 'bestglm', 'gaselect', 'glmnet', 'kableExtra', 'knitr', 'lme4', 'sensitivity', 'shrinkTVP', 'rmarkdown' VignetteBuilder package required for checking but not installed: ‘knitr’ Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.7.4
Check: examples
Result: ERROR Running examples in ‘tidyfit-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### 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 Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.7.4
Check: tests
Result: ERROR Running ‘testthat.R’ [13s/13s] 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-enet-8.R Saving _problems/test-enet-22.R Saving _problems/test-enet-35.R Saving _problems/test-glmm-5.R Saving _problems/test-glmm-19.R Saving _problems/test-lasso-8.R Saving _problems/test-lasso-22.R Saving _problems/test-lasso-35.R Saving _problems/test-ridge-8.R Saving _problems/test-ridge-22.R Saving _problems/test-ridge-35.R [ FAIL 16 | WARN 0 | SKIP 0 | PASS 115 ] ══ 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-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-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-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-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)) [ FAIL 16 | WARN 0 | SKIP 0 | PASS 115 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.7.4
Check: package vignettes
Result: NOTE Package has ‘vignettes’ subdirectory but apparently no vignettes. Perhaps the ‘VignetteBuilder’ information is missing from the DESCRIPTION file? Flavor: r-devel-linux-x86_64-debian-gcc