Package: regressinator 0.3.0

regressinator: Simulate and Diagnose (Generalized) Linear Models

Simulate samples from populations with known covariate distributions, generate response variables according to common linear and generalized linear model families, draw from sampling distributions of regression estimates, and perform visual inference on diagnostics from model fits.

Authors:Alex Reinhart [aut, cre]

regressinator_0.3.0.tar.gz
regressinator_0.3.0.zip(r-4.7-any)regressinator_0.3.0.zip(r-4.6-any)regressinator_0.3.0.zip(r-4.5-any)
regressinator_0.3.0.tgz(r-4.6-any)regressinator_0.3.0.tgz(r-4.5-any)
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regressinator_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
regressinator/json (API)

# Install 'regressinator' in R:
install.packages('regressinator', repos = c('https://capnrefsmmat.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/capnrefsmmat/regressinator/issues

Pkgdown/docs site:https://www.refsmmat.com

On CRAN:

Conda:

statistics

6.20 score 4 stars 40 scripts 345 downloads 21 exports 111 dependencies

Last updated from:daef2ab6a1. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK234
source / vignettesOK281
linux-release-x86_64OK225
macos-release-arm64OK194
macos-oldrel-arm64OK115
windows-develOK149
windows-releaseOK138
windows-oldrelOK157
wasm-releaseOK163

Exports:augment_longeraugment_quantileaugment_quantile_longerbin_by_intervalbin_by_quantilebinned_residualsby_levelcustom_familydecryptempirical_linkmodel_lineupols_with_errorparametric_boot_distributionpartial_residualspopulationpredictorresponserfactorsample_xsample_ysampling_distribution

Dependencies:apeaskpassbackportsbase64encbootbroombslibcachemclasscliclustercodetoolscommonmarkcpp11crosstalkcurldata.tableDEoptimRDHARMadigestdiptestdoParalleldplyrevaluatefarverfastmapflexmixfontawesomeforeachfpcfsgapgap.datasetsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttpuvhttrinsightisobanditeratorsjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclelme4lmtestmagrittrMASSMatrixmclustmemoisemgcvmimeminqamodeltoolsmomentsnlmenloptrnnetnullaboropensslotelpillarpkgconfigplotlyplyrprabcluspromisespurrrqgamR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrmarkdownrobustbaseS7sassscalesshinysourcetoolsstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtableyamlzoo

An introduction to the regressinator
Population setup | Custom response distributions | Categorical predictors | Sampling from the population | Fitting models | Producing diagnostics | Visual inference | Sampling distributions | Parametric bootstrapping
Rendered fromregressinator.Rmdusingknitr::rmarkdown

Last update: 2025-08-20
Started: 2022-07-29

Linear regression diagnostics
Residual plots | Partial residual plots | Detecting basic misspecification | Checking for interactions | Cook's distances | Residual Q-Q plots | A case study
Rendered fromlinear-regression-diagnostics.Rmdusingknitr::rmarkdown

Last update: 2025-08-20
Started: 2022-08-05

Diagnostics for other GLMs
Empirical link plots | Naive residual plots | Marginal model plots | Partial residuals | Binned residuals | Randomized quantile residuals | Limitations
Rendered fromother-glm-diagnostics.Rmdusingknitr::rmarkdown

Last update: 2025-05-08
Started: 2023-05-02

Logistic regression diagnostics
Empirical logit plots | Naive residual plots | Marginal model plots | Partial residuals | Binned residuals | Randomized quantile residuals
Rendered fromlogistic-regression-diagnostics.Rmdusingknitr::rmarkdown

Last update: 2025-05-08
Started: 2022-08-05