Software for discrete choice model estimation

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Most commercial statistics software packages offer build-in logit model estimation functions. Some academic researchers in economics and marketing science field provide their source codes for academic use.

Contents

Train's code

Prof. Ken Train offers his Matlab codes using both maximum likelihood estimation (MLE) and Bayesian approach for mixed logit model.


Lenk's Code

Prof. Peter Lenk offers his Gauss code using Bayesian methods for discrete choice model estimation.


Biogeme

A free software package provided by Prof. Michael Bierlaire using the maximum likelihood estimation for Generalized Extreme Value (GEV) models. It can be used for Multinomial Logit models, Nested logit models and other types of GEV models.


Discrete Choice Model (DCM) Package

A free software package written in Ox (or using OxMetrics) which is a commercial statistics programming language. It is provided by Matias Eklof at Uppsala University and Melvyn Weeks at University of Cambridge. However, the package has not been updated since August 2005.


Software Type User Interface Design Estimation Prediction Scalability Hierarchical Cost
Excel spreadsheet graphical no yes maybe poor no $
Stata (conditional logit) statistics package graphical no yes no no $
SAS statistics package code yes yes excellent no $
SPSS statistics package graphical no yes no no $
Sawtooth Software conjoint package graphical yes yes yes excellent available $$$
StatWizards/NLOGIT conjoint package graphical yes yes yes no $$$
NLOGIT logit model package code no yes no
R/bayesm statistics package code no yes no poor yes free
Ken Train's Code research code code no yes no yes free - require Matlab or Gauss
Peter Lenk's Code research code code yes free - require GAUSS
Biogeme research program input file no yes no free
DCM package statistics package code no yes no free - require Ox or OxMetrics4


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