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ChoiceModelR: Choice Modeling in R
Implements an MCMC algorithm to estimate a hierarchical multinomial logit model with a normal heterogeneity distribution. The algorithm uses a hybrid Gibbs Sampler with a random walk metropolis step for the MNL coefficients for each unit. Dependent variable may be discrete or continuous. Independent variables may be discrete or continuous with optional order constraints. Means of the distribution of heterogeneity can optionally be modeled as a linear function of unit characteristics variables.
Getting started
Browse package contents
Package details |
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| Author | Ryan Sermas [aut], John V Colias [ctb, cre], Decision Analyst, Inc. [cph] |
| Maintainer | John V Colias <jcolias@decisionanalyst.com> |
| License | GPL (>= 3) |
| Version | 1.3.1 |
| URL | https://www.decisionanalyst.com/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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