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choicer: Discrete Choice Models for Economic Applications
Fast estimation of discrete-choice models for applied economics. Frequentist likelihoods, analytical gradients, and Hessians are implemented in C++ with 'OpenMP' parallelism, scaling efficiently to specifications with many alternative-specific constants. Compiled Gibbs samplers provide Bayesian multinomial probit and hierarchical models. Post-estimation routines cover predicted shares, own- and cross-price elasticities, diversion ratios, willingness to pay, and welfare counterfactuals. Supports multinomial logit ('MNL'), mixed logit ('MXL'), nested logit ('NL'), Bayesian multinomial probit ('MNP'), and hierarchical Bayesian multinomial logit and probit ('HMNL', 'HMNP').
Getting started
Package overview
README.md
Bayesian multinomial probit
Choice-based sampling and WESML weights
Discrete choice from data to policy, in a dozen lines
Hierarchical Bayes: panel tastes, product effects, and entry
Mixed logit and preference heterogeneity
Multinomial logit
Nested logit and grouped substitution
Which standard errors, and when
Browse package contents
Package details |
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| Author | Fernando Cordeiro [aut, cre, cph] |
| Maintainer | Fernando Cordeiro <fernandolpcordeiro@gmail.com> |
| License | LGPL (>= 3) |
| Version | 0.2.1 |
| URL | https://github.com/fpcordeiro/choicer https://fpcordeiro.github.io/choicer/ |
| Package repository | View on CRAN |
| Installation |
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