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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.

Version: 0.1.3
Depends: R (≥ 4.1)
Imports: broom, cli, dplyr, ggplot2, insight, nullabor, purrr, rlang, tibble, tidyr, tidyselect
Suggests: rmarkdown, knitr, mvtnorm, palmerpenguins, patchwork, testthat (≥ 3.0.0)
Published: 2024-01-11
Author: Alex Reinhart ORCID iD [aut, cre]
Maintainer: Alex Reinhart <areinhar at stat.cmu.edu>
BugReports: https://github.com/capnrefsmmat/regressinator/issues
License: MIT + file LICENSE
URL: https://www.refsmmat.com/regressinator/, https://github.com/capnrefsmmat/regressinator
NeedsCompilation: no
Materials: README NEWS
CRAN checks: regressinator results

Documentation:

Reference manual: regressinator.pdf
Vignettes: Linear regression diagnostics
Logistic regression diagnostics
Diagnostics for other GLMs
An introduction to the regressinator

Downloads:

Package source: regressinator_0.1.3.tar.gz
Windows binaries: r-devel: regressinator_0.1.3.zip, r-release: regressinator_0.1.3.zip, r-oldrel: regressinator_0.1.3.zip
macOS binaries: r-release (arm64): regressinator_0.1.3.tgz, r-oldrel (arm64): regressinator_0.1.3.tgz, r-release (x86_64): regressinator_0.1.3.tgz, r-oldrel (x86_64): regressinator_0.1.3.tgz
Old sources: regressinator archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=regressinator to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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