simulate_beta

Samples beta from the proposal distribution in Section 2.2 of
Christen &amp; Fox (2010).

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

simulate_beta function

<dl><dt>at</dt>
<dd>Shape parameter `a_t` (default 6).</dd></dl>

Arguments

Simulate the beta parameter for the Traverse kernel — simulate_beta

<dl>

<dt>at</dt>
<dd>Shape parameter `a_t` (default 6).</dd>

</dl>

simulate_beta: Simulate the beta parameter for the Traverse kernel

Description

Usage

Value

Arguments