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 |