BiProbitPartial-package: BiProbitPartial: Bivariate Probit with Partial Observability
In BiProbitPartial: Bivariate Probit with Partial Observability
Description
A suite of functions to estimate, summarize
and perform predictions with the bivariate probit subject to partial observability.
The frequentist and Bayesian probabilistic philosophies are both supported. The
frequentist method is estimated with maximum likelihood and the Bayesian method is
estimated with a Markov Chain Monte Carlo (MCMC) algorithm developed by
Rajbanhdari, A (2014) <doi:10.1002/9781118771051.ch13>.
BiProbitPartial documentation built on May 2, 2019, 1:48 p.m.
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Description
A suite of functions to estimate, summarize and perform predictions with the bivariate probit subject to partial observability. The frequentist and Bayesian probabilistic philosophies are both supported. The frequentist method is estimated with maximum likelihood and the Bayesian method is estimated with a Markov Chain Monte Carlo (MCMC) algorithm developed by Rajbanhdari, A (2014) <doi:10.1002/9781118771051.ch13>.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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