R package 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.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Frits Traets, Daniel Gil Sanchez, Martina Vandebroek: Generating Optimal Designs for Discrete Choice Experiments in R: The idefix Package (2020) not zbMATH
- Mauricio Sarrias and Ricardo Daziano: Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package (2017) not zbMATH