In 1999 Simo Särkkä implemented several Markov chain Monte Carlo (MCMC) convergence diagnostics in Matlab at Laboratory of Computational Engineering. Later Aki Vehtari added additonal functions, fixed bugs and improved the documentation.
This software is distributed under the GNU General Public Licence (version 2 or later); please refer to the file Licence.txt, included with the software, for details.
Convergence diagnostics PSRF - Gelman-Rubin Potential Scale Reduction Factor CPSRF - Cumulative Potential Scale Reduction Factor MPSRF - Multivariate Potential Scale Reduction Factor CMPSRF - Cumulative Multivariate Potential Scale Reduction Factor IPSRF - Interval-based Potential Scale Reduction Factor CIPSRF - Cumulative Interval-based Potential Scale Reduction Factor KS - Kolmogorov-Smirnov goodness-of-fit hypothesis test HAIR - Brooks' hairiness convergence diagnostic CUSUM - Yu-Mykland convergence diagnostic for MCMC SCORE - Calculate score-function convergence diagnostic GBINIT - Initial iterations for Gibbs iteration diagnostic GBITER - Estimate number of additional Gibbs iterations Time series analysis ACORR - Estimate autocorrelation function of time series ACORRTIME - Estimate autocorrelation evolution of time series (simple) GEYER_ICSE - Compute autocorrelation time tau using Geyer's initial convex sequence estimator (requires Optimization toolbox) GEYER_IMSE - Compute autocorrelation time tau using Geyer's initial monotone sequence estimator Kernel density estimation etc.: KERNEL1 - 1D Kernel density estimation of data KERNELS - Kernel density estimation of independent components of data KERNELP - 1D Kernel density estimation, with automatic kernel width NDHIST - Normalized histogram of N-dimensional data HPDI - Estimates the Bayesian HPD intervals Manipulation of MCMC chains THIN - Delete burn-in and thin in MCMC-chains JOIN - Join similar structures of arrays to one structure of arrays Misc: CUSTATS - Calculate cumulative statistics of data