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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: 0.2.0
Depends: R (≥ 4.1)
Imports: broom, cli, DHARMa, dplyr, ggplot2, insight, nullabor, purrr, rlang, tibble, tidyr, tidyselect
Suggests: rmarkdown, knitr, mvtnorm, palmerpenguins, patchwork, testthat (≥ 3.0.0)
Published: 2024-08-16
DOI: 10.32614/CRAN.package.regressinator
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 (source, R code)
Logistic regression diagnostics (source, R code)
Diagnostics for other GLMs (source, R code)
An introduction to the regressinator (source, R code)

Downloads:

Package source: regressinator_0.2.0.tar.gz
Windows binaries: r-devel: regressinator_0.2.0.zip, r-release: regressinator_0.2.0.zip, r-oldrel: regressinator_0.2.0.zip
macOS binaries: r-release (arm64): regressinator_0.2.0.tgz, r-oldrel (arm64): regressinator_0.2.0.tgz, r-release (x86_64): regressinator_0.2.0.tgz, r-oldrel (x86_64): regressinator_0.2.0.tgz
Old sources: regressinator archive

Linking:

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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.