Software

endorse: Bayesian Measurement Models for Analyzing Endorsement Experiments

Fit the hierarchical and non-hierarchical Bayesian measurement models proposed by Bullock, Imai, and Shapiro (2011) <doi:10.1093/pan/mpr031> to analyze endorsement experiments. Endorsement experiments are a survey methodology for eliciting truthful responses to sensitive questions. This methodology is helpful when measuring support for socially sensitive political actors such as militant groups. The model is fitted with a Markov chain Monte Carlo algorithm and produces the output containing draws from the posterior distribution.

• Yuki Shiraito [aut, cre], Kosuke Imai [aut], Bryn Rosenfeld [ctb]
• CRAN - Package endorse
• GitHub repository

poisbinom: A Faster Implementation of the Poisson-Binomial Distribution

Provides the probability, distribution, and quantile functions and random number generator for the Poisson-Binomial distribution. This package relies on FFTW to implement the discrete Fourier transform, so that it is much faster than the existing implementation of the same algorithm in R.

• Santiago Olivella [aut, cre], Yuki Shiraito [aut, cre]
• CRAN - Package poisbinom
• GitHub repository