This package tunes a symmetric random walk Metropolis algorithm with Gaussian proposals via finite MCMC adaption combined with new adaptive diagnostics, and it runs the tuned algorithm to converge to a target distribution and estimate the stationary mean of a functional.
|License:||GPL (>= 2)|
The main function is ‘atmcmc’, which is to run a MCMC algorithm with adaptive schemes and diagnostics embedded. ‘plotmcmc’ function is to get traceplots and histograms of output from an ‘atmcmc’ run. ‘summarymcmc’ function displays summary statistics from the output.
Maintainer: Jinyoung Yang <email@example.com>
Jinyoung Yang and Jeffrey S. Rosenthal. Automatically Tuned General-Purpose MCMC via New Convergence Diagnostics. Preprint, 2014.
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