calculate_diagnostics

Computes posterior summaries (mean, SD, quantiles) and
effective sample sizes after discarding a burn-in fraction.

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

calculate_diagnostics function

<dl><dt>samples</dt>
<dd>Matrix of MCMC samples (iterations x parameters).</dd>
<dt>burnin_frac</dt>
<dd>Fraction of samples to discard as burn-in.</dd>
<dt>param_names</dt>
<dd>Optional character vector of parameter names.</dd>
<dt>title</dt>
<dd>Optional title for printed output.</dd></dl>

Arguments

Calculate MCMC diagnostics — calculate_diagnostics

<dl>

<dt>samples</dt>
<dd>Matrix of MCMC samples (iterations x parameters).</dd>


<dt>burnin_frac</dt>
<dd>Fraction of samples to discard as burn-in.</dd>


<dt>param_names</dt>
<dd>Optional character vector of parameter names.</dd>


<dt>title</dt>
<dd>Optional title for printed output.</dd>

</dl>

calculate_diagnostics: Calculate MCMC diagnostics

Description

Usage

Value

Arguments

Examples