sampleAlpha

Sample \(\alpha\) conditional on the current
partition and value of \(K\) using an Metropolis-Hastings
step with log-normal proposal.

internal

Fits Bayesian finite mixtures with an unknown number of components using the telescoping sampler and different component distributions. For more details see Frühwirth-Schnatter et al. (2021) <doi:10.1214/21-BA1294>.

Gertraud Malsiner-Walli

telescope

Bayesian Mixtures with an Unknown Number of Components

Bettina Grün

Sylvia Frühwirth-Schnatter

sampleAlpha function

<dl><dt>N</dt>
<dd>A number; indicating the sample size.</dd>
<dt>Nk</dt>
<dd>An integer vector; indicating the group sizes in the partition.</dd>
<dt>K</dt>
<dd>A number; indicating the number of components.</dd>
<dt>alpha</dt>
<dd>A numeric value; indicating the value for \(\alpha\).</dd>
<dt>s0_proposal</dt>
<dd>A numeric value; indicating the standard deviation of the random walk.</dd>
<dt>log_pAlpha</dt>
<dd>A function; evaluating the log prior of \(\alpha\).</dd></dl>

Arguments

Sample alpha conditional on partition and K using an
Metropolis-Hastings step with log-normal proposal. — sampleAlpha

<dl>

<dt>N</dt>
<dd>A number; indicating the sample size.</dd>


<dt>Nk</dt>
<dd>An integer vector; indicating the group sizes in the partition.</dd>


<dt>K</dt>
<dd>A number; indicating the number of components.</dd>


<dt>alpha</dt>
<dd>A numeric value; indicating the value for \(\alpha\).</dd>


<dt>s0_proposal</dt>
<dd>A numeric value; indicating the standard deviation of the random walk.</dd>


<dt>log_pAlpha</dt>
<dd>A function; evaluating the log prior of \(\alpha\).</dd>

</dl>

sampleAlpha: Sample alpha conditional on partition and K using an Metropolis-Hastings step with log-normal proposal.

Description

Usage

Value

Arguments