mlogit: Multinomial Logit Models

Maximum likelihood estimation of random utility discrete choice models. The software is described in Croissant (2020) <doi:10.18637/jss.v095.i11> and the underlying methods in Train (2009) <doi:10.1017/CBO9780511805271>.

Version: 1.1-1
Depends: R (≥ 2.10), dfidx
Imports: Formula, zoo, lmtest, statmod, MASS, Rdpack
Suggests: knitr, car, nnet, lattice, AER, ggplot2, texreg, rmarkdown
Published: 2020-10-02
Author: Yves Croissant [aut, cre]
Maintainer: Yves Croissant <yves.croissant at univ-reunion.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://cran.r-project.org/package=mlogit, https://r-forge.r-project.org/projects/mlogit/
NeedsCompilation: no
Citation: mlogit citation info
Materials: NEWS
In views: Econometrics
CRAN checks: mlogit results

Documentation:

Reference manual: mlogit.pdf
Vignettes: 2. Data management, model description and testing
3. Random utility model and the multinomial logit model
4. Logit models relaxing the iid hypothesis
5. The random parameters (or mixed) logit model
6. The multinomial probit model
7. Miscellaneous models
Exercise 1: Multinomial logit model
Exercise 2: Nested logit model
Exercise 3: Mixed logit model
Exercise 4: Multinomial probit
mlogit

Downloads:

Package source: mlogit_1.1-1.tar.gz
Windows binaries: r-devel: mlogit_1.1-1.zip, r-release: mlogit_1.1-1.zip, r-oldrel: mlogit_1.1-1.zip
macOS binaries: r-release (arm64): mlogit_1.1-1.tgz, r-oldrel (arm64): mlogit_1.1-1.tgz, r-release (x86_64): mlogit_1.1-1.tgz
Old sources: mlogit archive

Reverse dependencies:

Reverse depends: nopp, Ravages
Reverse imports: clusterSEs, DCEmgmt, DCEtool, ExactMed, glm.predict, gmnl, misclassGLM, pleLMA, riskclustr
Reverse suggests: AER, broom, catdata, dfidx, generalhoslem, gofcat, insight, lmw, logitr, marginaleffects, micsr, mixl, mlogitBMA, nonnest2, performance, plot3logit, RprobitB, support.BWS, urbin, WeightIt
Reverse enhances: prediction, stargazer, texreg

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mlogit to link to this page.