Maximum likelihood estimation of random utility discrete choice models. The software is described in Croissant (2020) and the underlying methods in Train (2009) .
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2.0-0 by Yves Croissant, 5 months ago
https://cran.r-project.org/package=mlogit
Browse source code at https://github.com/cran/mlogit
Authors: Yves Croissant [aut, cre]
Documentation: PDF Manual
GPL (>= 2) license
Imports Formula, lmtest, Rdpack, dfidx, micsr, numDeriv
Suggests knitr, car, nnet, lattice, AER, ggplot2, quarto, dplyr
Imported by DCEmgmt, ExactMed, glm.predict, gmnl, misclassGLM, pleLMA, riskclustr.
Depended on by Ravages, clusterSEs.
Suggested by AER, DCEtool, Dyn4cast, RprobitB, WeightIt, broom, catdata, choicedata, generalhoslem, ggeffects, gofcat, insight, lmw, logitr, marginaleffects, micsr, mixl, mlogitBMA, nestedLogit, nonnest2, performance, plot3logit, spicy, support.BWS, urbin.
Enhanced by prediction, stargazer, texreg.
See at CRAN