ConvertChains

start

<p>a Boolean switch to make posterior log likelihood</p>

<p>Convert MCMC chains to a data frame for plotting</p>

Hierarchical Bayesian modelling. The 'ggdmc' package provides tools designed for fitting cognitive models, using population-based Markov Chain Monte Carlo (pMCMC) and fast C++ libraries. The paper by Heathcote, Lin, Reynolds, Strickland, Gretton, and Matzke (2018, <doi:10.3758/s13428-018-1067-y>) describes the early prototype of the package (by the version 0.4.2). The paper accompanied with the revamped latest version (> 0.2.4.5) is under preparation Lin, Strickland, Reynold, and Heathcote (2018) and a further paper regarding the new pMCMC sampling modified based on Hu and Tsai's (2010) work is also under preparation. See 'citation("ggdmc")' for details.

Yi-Shin Lin

ConvertChains: Prepare posterior samples for plotting version 1

Description

Usage

Arguments