twalk_move

Selects one of the four kernels, generates a proposal, and calculates
the Metropolis-Hastings acceptance probability.

internal

Implements the t-walk algorithm, a general-purpose, self-adjusting
Markov Chain Monte Carlo (MCMC) sampler for continuous distributions as
described by Christen & Fox (2010) <doi:10.1214/10-BA603>. The t-walk requires
no tuning and is robust for a wide range of target distributions, including
high-dimensional and multimodal problems. This implementation includes an
option for running multiple chains in parallel to accelerate sampling and
facilitate convergence diagnostics.

Rodrigo Fonseca Villa

Rtwalk

An MCMC Sampler Using the t-Walk Algorithm

twalk_move function

<dl><dt>...</dt>
<dd>Arguments passed to `log_post_fun` and `support_fun`.</dd></dl>

Arguments

Run a single t-walk move (step) — twalk_move

<dl>

<dt>...</dt>
<dd>Arguments passed to `log_post_fun` and `support_fun`.</dd>

</dl>

twalk_move: Run a single t-walk move (step)

Description

Usage

Value

Arguments