Discrete Choice (Binary, Poisson and Ordered) Models with Random Parameters

An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data.

Rchoice is a package in R for estimating Ordered, Binary and Poisson models with random parameters for cross-sectional and panel data.

What kind of models can be estimated?

  • Binary (Logit/Probit), Ordered (Logit/Probit) and Poisson Models with fixed (non-stochastic) parameters
  • Binary (Logit/Probit), Ordered (Logit/Probit) and Poisson models with random coefficients. The distribution of the coefficients can be normal, log-normal, truncated normal, triangular, uniform and Johnson Sb.
  • Random Effects model for Panel or longitudinal data
  • Estimate the conditional individual-specific coefficient


Reference manual

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0.3-2 by Mauricio Sarrias, 6 months ago


Browse source code at https://github.com/cran/Rchoice

Authors: Mauricio Sarrias <[email protected]>

Documentation:   PDF Manual  

Task views: Econometrics

GPL (>= 2) license

Imports msm, plm, plotrix, stats, graphics

Depends on Formula, maxLik

Suggests car, lmtest, memisc, pglm, sandwich

See at CRAN