GlmSimulatoR: Creates Ideal Data for Generalized Linear Models

Have you ever struggled to find "good data" for a generalized linear model? Would you like to test how quickly statistics converge to parameters, or learn how picking different link functions affects model performance? This package creates ideal data for both common and novel generalized linear models so your questions can be empirically answered.

Version: 0.1.0
Imports: assertthat, stats, purrr, stringr, dplyr, statmod, magrittr, rlang, ggplot2, MASS
Suggests: testthat, knitr, rmarkdown
Published: 2019-08-12
Author: Greg McMahan
Maintainer: Greg McMahan <gmcmacran at>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: GlmSimulatoR results


Reference manual: GlmSimulatoR.pdf
Vignettes: Dealing With Right Skewed Data
Forward Stepwise Search
Package source: GlmSimulatoR_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: GlmSimulatoR_0.1.0.tgz, r-oldrel: GlmSimulatoR_0.1.0.tgz


Please use the canonical form to link to this page.