An Interface to Statistical Modeling Independent of Model Architecture

Provides functions for evaluating, displaying, and interpreting statistical models. The goal is to abstract the operations on models from the particular architecture of the model. For instance, calculating effect sizes rather than looking at coefficients. The package includes interfaces to both regression and classification architectures, including lm(), glm(), rlm() in 'MASS', random forests and recursive partitioning, k-nearest neighbors, linear and quadratic discriminant analysis, and models produced by the 'caret' package's train(). It's straightforward to add in other other model architectures.


Reference manual

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0.3.0 by Daniel Kaplan, 4 years ago

Browse source code at

Authors: Kaplan Daniel [aut, cre] , Pruim Randall [aut, cre]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports caret, ggplot2, ggformula, lazyeval, knitr, MASS, testthat, tibble, tidyr, tidyverse

Depends on mosaicCore, splines, dplyr

Suggests mosaic, mosaicData, randomForest, rpart

See at CRAN