BayesPostEst

An implementation of functions to generate and plot postestimation quantities after estimating Bayesian regression models using Markov chain Monte Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves (see Beger, 2016 doi:10.2139/ssrn.2765419), the implementation of the observed values method of calculating predicted probabilities by Hanmer and Kalkan (2013) doi:10.1111/j.1540-5907.2012.00602.x), the implementation of the average value method of calculating predicted probabilities (see King, Tomz, and Wittenberg, 2000 doi:10.2307/2669316), and the generation and plotting of first differences to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; King, Tomz, and Wittenberg, 2000 doi:10.2307/2669316). This package can be used with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.

Last 30 days

This package has been downloaded 396 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,955 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 35 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.