5 packages on CRAN
Software to implement methodology to preform automatic response category combinations in multinomial logistic regression. There are functions for both cross validation and AIC for model selection. The method provides regression coefficient estimates that may be useful for better understanding the true probability distribution of multinomial logistic regression when category probabilities are similar. These methods are not recommended for a large number of predictor variables.
Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, in press.
Datasets to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage (forthcoming).
Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.
Fits the Multivariate Cluster Elastic Net (MCEN) presented in Price & Sherwood (2018) <arXiv:1707.03530>. The MCEN model simultaneously estimates regression coefficients and a clustering of the responses for a multivariate response model. Currently accommodates the Gaussian and binomial likelihood.