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Bayesian Estimation of Probit Unfolding Models

Description

pumBayes is an R package designed for Bayesian estimation of probit unfolding models (PUM) for binary preference data. The package is publicly available and can be cited using the following DOI: 10.5281/zenodo.15069856.

Installation

You can install the stable version of pumBayes from CRAN:

install.packages("pumBayes")

Or install the development version from GitHub:

install.packages("devtools")
library(devtools)
install_github("SkylarShiHub/pumBayes")

Documentation

CRAN page: https://cran.r-project.org/package=pumBayes

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Version

Install

install.packages('pumBayes')

Monthly Downloads

121

Version

1.0.1

License

GPL-3

Issues

Pull Requests

Stars

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Maintainer

Skylar Shi

Last Published

October 23rd, 2025

Functions in pumBayes (1.0.1)

predict_irt

Calculate Probabilities for Dynamic Item Response Theory Model
predict_pum

Calculate Probabilities for Probit Unfolding Models
sample_pum_dynamic

Generate posterior samples from the dynamic probit unfolding model
dtnorm

Density Function for Truncated Normal Distribution
predict_ideal

Calculate Probabilities for the IDEAL Model
preprocess_rollcall

Preprocess Roll Call Data
item_char

Generate Data for Item Characteristic Curves
post_rank

Generate Quantile Ranks for Legislators
calc_waic

Calculate a block version of Watanabe-Akaike Information Criterion (WAIC)
h116

116th U.S. House of Representatives Roll Call Votes
tune_hyper

Generate Probability Samples for Voting "Yes"
sample_pum_static

Generate posterior samples from the static probit unfolding model
scotus.1937.2021

U.S. Supreme Court Voting Data (1937-2021)