mnlogit: Multinomial Logit Model

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.

AuthorAsad Hasan, Wang Zhiyu, Alireza S. Mahani
Date of publication2016-11-08 10:56:49
MaintainerAsad Hasan <asadhasan32@gmail.com>
LicenseGPL (>= 2)
Version1.2.5

View on CRAN

Functions

coef.mnlogit Man page
df.residual.mnlogit Man page
Fish Man page
Fishing Man page
fitted.mnlogit Man page
hmftest Man page
hmftest.formula Man page
hmftest.mnlogit Man page
index Man page
index.mnlogit Man page
logLik.mnlogit Man page
lrtest Man page
lrtest.mnlogit Man page
mnlogit Man page
predict.mnlogit Man page
print.est.stats Man page
print.mnlogit Man page
print.model.size Man page
print.summary.mnlogit Man page
residuals.mnlogit Man page
scoretest Man page
scoretest.mnlogit Man page
summary.mnlogit Man page
terms.mnlogit Man page
update.mnlogit Man page
vcov.mnlogit Man page
waldtest Man page
waldtest.mnlogit Man page

Files

mnlogit
mnlogit/inst
mnlogit/inst/CITATION
mnlogit/inst/doc
mnlogit/inst/doc/mnlogit.R
mnlogit/inst/doc/mnlogit.Rnw
mnlogit/inst/doc/mnlogit.pdf
mnlogit/src
mnlogit/src/Makevars
mnlogit/src/hessian.cc
mnlogit/src/hessian.h
mnlogit/NAMESPACE
mnlogit/data
mnlogit/data/Fish.rda
mnlogit/R
mnlogit/R/hyptests.R mnlogit/R/mnlogit.methods.R mnlogit/R/mnlogit.R mnlogit/R/formula.R mnlogit/R/predict.R mnlogit/R/newton.R mnlogit/R/likelihood.R mnlogit/R/zzz.R
mnlogit/vignettes
mnlogit/vignettes/mnlogit.Rnw
mnlogit/vignettes/simChoiceModel.R
mnlogit/vignettes/table2_Code.R
mnlogit/vignettes/fig1_Code.R
mnlogit/vignettes/mnlogit.bib
mnlogit/vignettes/HessSpeedups.pdf
mnlogit/MD5
mnlogit/build
mnlogit/build/vignette.rds
mnlogit/DESCRIPTION
mnlogit/ChangeLog
mnlogit/man
mnlogit/man/hyptests.Rd mnlogit/man/mnlogit.Rd mnlogit/man/Fish.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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