Time and memory efficient estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed by Newton-Raphson method using an optimized, parallel C++ library to achieve fast computation of Hessian matrices. Motivated by large scale multiclass classification problems in econometrics and machine learning.
Version: | 1.2.0 |
Imports: | mlogit, lmtest, Formula |
Suggests: | VGAM, nnet |
Published: | 2014-09-10 |
Author: | Asad Hasan, Wang Zhiyu, Alireza S. Mahani |
Maintainer: | Asad Hasan <asad.hasan at sentrana.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | ChangeLog |
In views: | Econometrics |
CRAN checks: | mnlogit results |
Reference manual: | mnlogit.pdf |
Vignettes: |
Fast Estimation of Multinomial Logit Models: R package mnlogit |
Package source: | mnlogit_1.2.0.tar.gz |
Windows binaries: | r-devel: mnlogit_1.2.0.zip, r-release: mnlogit_1.2.0.zip, r-oldrel: mnlogit_1.2.0.zip |
OS X Snow Leopard binaries: | r-release: mnlogit_1.2.0.tgz, r-oldrel: mnlogit_1.2.0.tgz |
OS X Mavericks binaries: | r-release: mnlogit_1.2.0.tgz |
Old sources: | mnlogit archive |
Reverse enhances: | texreg |