new_mcmcRocPrc

a <code>\[N, iter\]</code> matrix of predicted probabilities

pred_prob

a <code>numeric(N)</code> vector of observed outcomes

yvec

curves

collapse posterior samples into single summary?

fullsims

This function actually does the heavy lifting once we have a matrix of
predicted probabilities from a model, plus the vector of observed outcomes.
The reason to have it here in a single function is that we don't replicate
it in each function that accomodates a JAGS, BUGS, RStan, etc. object.

internal

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'.

new_mcmcRocPrc: Constructor for mcmcRocPrc objects

Description

Usage

Arguments