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.


Reference manual

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0.2.4 by Greg McMahan, 8 months ago

Browse source code at

Authors: Greg McMahan

Documentation:   PDF Manual  

GPL-3 license

Imports assertthat, stats, purrr, stringr, dplyr, statmod, magrittr, MASS, tweedie, ggplot2, cplm

Suggests testthat, knitr, rmarkdown, covr

See at CRAN