R: Bayesian Estimation of Probit Unfolding Models for Binary Preference Data

# Bayesian Estimation of Probit Unfolding Models for Binary Preference Data

## Documentation for package ‘pumBayes’ version 1.0.2

- DESCRIPTION file
- Package README

## Help Pages

calc_waic | Calculate a block version of Watanabe-Akaike Information Criterion (WAIC)
dtnorm | Density Function for Truncated Normal Distribution
h116 | 116th U.S. House of Representatives Roll Call Votes
item_char | Generate Data for Item Characteristic Curves
mqTime | U.S. Supreme Court Voting Data (1937-2021)
mqVotes | U.S. Supreme Court Voting Data (1937-2021)
post_rank | Generate Quantile Ranks for Legislators
predict_ideal | Calculate Probabilities for the IDEAL Model
predict_irt | Calculate Probabilities for Dynamic Item Response Theory Model
predict_pum | Calculate Probabilities for Probit Unfolding Models
preprocess_rollcall | Preprocess Roll Call Data
sample_pum_dynamic | Generate posterior samples from the dynamic probit unfolding model
sample_pum_static | Generate posterior samples from the static probit unfolding model
scotus.1937.2021 | U.S. Supreme Court Voting Data (1937-2021)
tune_hyper | Generate Probability Samples for Voting "Yes"