Software for discrete choice model estimation
From DDL Wiki
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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. | 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. | ||
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{| class="wikitable" border="1" cellpadding="2" cellspacing="0" | {| class="wikitable" border="1" cellpadding="2" cellspacing="0" | ||
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| statistics package || code || yes || yes || || excellent || no || $ | | statistics package || code || yes || yes || || excellent || no || $ | ||
|- | |- | ||
| - | ! Stata | + | ! Stata |
| statistics package || graphical || no || yes || no || || no || $ | | statistics package || graphical || no || yes || no || || no || $ | ||
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| conjoint package || graphical || yes || yes || yes || excellent || available || $$$ | | conjoint package || graphical || yes || yes || yes || excellent || available || $$$ | ||
|- | |- | ||
| - | ! | + | ! LIMDEP/NLOGIT |
| conjoint package || graphical || yes || yes || yes || || no || $$$ | | conjoint package || graphical || yes || yes || yes || || no || $$$ | ||
|- | |- | ||
| - | ! NLOGIT | + | ! LIMDEP/NLOGIT |
| logit model package || code || no || yes || || || no || | | logit model package || code || no || yes || || || no || | ||
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| statistics package || code || no || yes || no || || || free - require Ox or OxMetrics4 | | statistics package || code || no || yes || no || || || free - require Ox or OxMetrics4 | ||
|} | |} | ||
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| + | ==Excel== | ||
| + | Excel is the popular spreadsheet software. With well understanding of choice model structure, the discrete choice results can be transformed into a maximum likelihood problem (log-likelihood), which is solvable by Excel build-in solver. However, such approach is not suitable for the logit models with random coefficients since the construction of random draws for simulation is tedious in spreadsheets. | ||
| + | |||
| + | *[http://www.cmu.edu/me/ddl/resources.html Prof. Jeremy Michalek's website] provides his logit regression spreadsheet for model in his paper "Linking marketing and engineering product design decisions via analytical target cascading," Journal of Product Innovation Management, 2005, v22 p42-62. | ||
| + | |||
| + | ==SAS/MDC== | ||
| + | SAS is a powerful software package for statistical application. The MDC (Multinomial Discrete Choice) module is capable to perform choice model regression for various discrete models, such as conditional logit, heteroscedastic extreme value, mixed logit, nested logit, and multinomial probit models. | ||
| + | |||
| + | *[http://support.sas.com/rnd/app/papers/mdc.pdf SAS/MDC Documentation] | ||
| + | *[http://www.ats.ucla.edu/stat/SAS/faq/clogit.htm Logit model regression in SAS] in UCLA SAS FAQ website | ||
| + | |||
| + | ==LIMDEP/NLOGIT== | ||
| + | NLOGIT is an extension program of commercial LIMDEP statistical software. It provides the functions for estimation, model simulation and analysis of multinomial choice data. According to the company website, the latest version of NLOGIT is able to handle heterogeneity in variances of utility functions and mixed logit model. | ||
| + | |||
| + | *[http://www.limdep.com/ LIMDEP/NLOGIT website] | ||
| + | |||
| + | ==Train's code== | ||
| + | Prof. Ken Train offers his Matlab codes using both maximum likelihood estimation (MLE) and Bayesian approach for mixed logit model. He also provided the old Gauss codes using MLE for mixed logit estimation. Train's Gauss code has been modified and applied to a study about multiparty elections by [http://www.polsci.ucsb.edu/faculty/glasgow/papers.html Prof. Glasgow Garrett], where his code and data are provided. | ||
| + | |||
| + | *[http://elsa.berkeley.edu/~train/ Prof. Ken Train's website] | ||
| + | |||
| + | ==Lenk's Code== | ||
| + | Prof. Peter Lenk offers his Gauss code using Bayesian methods for discrete choice model estimation. | ||
| + | *[http://webuser.bus.umich.edu/plenk/index.htm Prof. Peter Lenk's website] | ||
| + | |||
| + | ==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. | ||
| + | *[http://transp-or.epfl.ch/page63023.html Biogeme] | ||
| + | |||
| + | ==DCM Package== | ||
| + | DCM stands for Discrete Choice Model. It is free software package written in Ox (a substitute called [http://www.oxmetrics.net/ OxMetrics] has trial version available) 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. | ||
| + | *[http://www.econ.cam.ac.uk/DCM/DCMWebPage.htm DCM package V1.1] | ||
==External Links== | ==External Links== | ||
*[http://www.indiana.edu/~statmath/stat/all/cdvm/cdvm6.html Multinomial Logit Regression using STATA, SAS/CATMOD, LIMDEP and SPSS] | *[http://www.indiana.edu/~statmath/stat/all/cdvm/cdvm6.html Multinomial Logit Regression using STATA, SAS/CATMOD, LIMDEP and SPSS] | ||
*[http://www.core.ucl.ac.be/~laurent/M@ximize/index.html '''M@ximize''' - a free maximum likelihood package for OxGauss] | *[http://www.core.ucl.ac.be/~laurent/M@ximize/index.html '''M@ximize''' - a free maximum likelihood package for OxGauss] | ||
Revision as of 22:08, 26 October 2007
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.
| Software | Type | User Interface | Design | Estimation | Prediction | Scalability | Hierarchical | Cost |
|---|---|---|---|---|---|---|---|---|
| Excel | spreadsheet | graphical | no | yes | maybe | poor | no | $ |
| SAS/MDC | statistics package | code | yes | yes | excellent | no | $ | |
| Stata | statistics package | graphical | no | yes | no | no | $ | |
| SPSS | statistics package | graphical | no | yes | no | no | $ | |
| Sawtooth Software | conjoint package | graphical | yes | yes | yes | excellent | available | $$$ |
| LIMDEP/NLOGIT | conjoint package | graphical | yes | yes | yes | no | $$$ | |
| LIMDEP/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 |
Contents |
Excel
Excel is the popular spreadsheet software. With well understanding of choice model structure, the discrete choice results can be transformed into a maximum likelihood problem (log-likelihood), which is solvable by Excel build-in solver. However, such approach is not suitable for the logit models with random coefficients since the construction of random draws for simulation is tedious in spreadsheets.
- Prof. Jeremy Michalek's website provides his logit regression spreadsheet for model in his paper "Linking marketing and engineering product design decisions via analytical target cascading," Journal of Product Innovation Management, 2005, v22 p42-62.
SAS/MDC
SAS is a powerful software package for statistical application. The MDC (Multinomial Discrete Choice) module is capable to perform choice model regression for various discrete models, such as conditional logit, heteroscedastic extreme value, mixed logit, nested logit, and multinomial probit models.
- SAS/MDC Documentation
- Logit model regression in SAS in UCLA SAS FAQ website
LIMDEP/NLOGIT
NLOGIT is an extension program of commercial LIMDEP statistical software. It provides the functions for estimation, model simulation and analysis of multinomial choice data. According to the company website, the latest version of NLOGIT is able to handle heterogeneity in variances of utility functions and mixed logit model.
Train's code
Prof. Ken Train offers his Matlab codes using both maximum likelihood estimation (MLE) and Bayesian approach for mixed logit model. He also provided the old Gauss codes using MLE for mixed logit estimation. Train's Gauss code has been modified and applied to a study about multiparty elections by Prof. Glasgow Garrett, where his code and data are provided.
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.
DCM Package
DCM stands for Discrete Choice Model. It is free software package written in Ox (a substitute called OxMetrics has trial version available) 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.
