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BiProbitPartial: Bivariate Probit with Partial Observability
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>.
Getting started
Browse package contents
Package details |
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| Author | Michael Guggisberg and Amrit Romana |
| Maintainer | Michael Guggisberg <mguggisb@ida.org> |
| License | GPL-3 |
| Version | 1.0.3 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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