CRAN/E | BiProbitPartial

BiProbitPartial

Bivariate Probit with Partial Observability

Installation

About

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.

Key Metrics

Version 1.0.3
Published 2019-01-10 1922 days ago
Needs compilation? yes
License GPL-3
CRAN checks BiProbitPartial results

Downloads

Yesterday 0
Last 7 days 4 -50%
Last 30 days 27 -18%
Last 90 days 159 -15%
Last 365 days 1.481 -52%

Maintainer

Maintainer

Michael Guggisberg

mguggisb@ida.org

Authors

Michael Guggisberg
Amrit Romana

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

BiProbitPartial archive

Depends

numDeriv ≥ 2016.8-1

Imports

Rcpp ≥ 0.12.19
Formula ≥ 1.2-3
optimr ≥ 2016-8.16
pbivnorm ≥ 0.6.0
mvtnorm ≥ 1.0-8
RcppTN ≥ 0.2-2
coda ≥ 0.19-2

Suggests

sampleSelection

LinkingTo

Rcpp
RcppArmadillo
RcppTN