compute_r_eff

Compute relative effective sample size for log-likelihood

internal

Fits cumulative link models (CLMs) for ordinal categorical data
using 'CmdStanR'. Supports various link functions including logit, probit,
cloglog, loglog, cauchit, and flexible parametric links such as
Generalized Extreme Value (GEV), Asymmetric Exponential Power (AEP),
and Symmetric Power. Models are pre-compiled using the 'instantiate'
package for fast execution without runtime compilation. Methods are
described in Agresti (2010, ISBN:978-0-470-08289-8),
Wang and Dey (2011) <doi:10.1007/s10651-010-0154-8>, and
Naranjo, Perez, and Martin (2015) <doi:10.1007/s11222-014-9449-1>.

Tomotaka Momozaki

clmstan

Cumulative Link Models with 'CmdStanR'

compute_r_eff function

<dl><dt>object</dt>
<dd>A clmstan object</dd>
<dt>log_lik</dt>
<dd>Log-likelihood matrix (S x N)</dd>
<dt>cores</dt>
<dd>Number of cores for parallel computation</dd></dl>

Arguments

Compute relative effective sample size for log-likelihood — compute_r_eff

<dl>

<dt>object</dt>
<dd>A clmstan object</dd>


<dt>log_lik</dt>
<dd>Log-likelihood matrix (S x N)</dd>


<dt>cores</dt>
<dd>Number of cores for parallel computation</dd>

</dl>

compute_r_eff: Compute relative effective sample size for log-likelihood

Description

Usage

Value

Arguments