logacceptance_ratio_logu

This function computes the Metropolis-Hastings ratio to decide whether to accept or reject a new value for logU.

internal

Bayesian nonparametric density estimation modeling mixtures by a Ferguson-Klass type algorithm for posterior normalized random measures.

Guillaume Kon Kam King

BNPdensity

Ferguson-Klass Type Algorithm for Posterior Normalized Random
Measures

Julyan Arbel

Ernesto Barrios

Antonio Lijoi

Luis E. Nieto-Barajas

Igor Prünster

logacceptance_ratio_logu function

<dl><dt>logu</dt>
<dd>Real, log of the latent variable U at the current iteration.</dd>
<dt>logu_prime</dt>
<dd>Real, log of the new proposed latent variable U.</dd>
<dt>n</dt>
<dd>Integer, number of data points.</dd>
<dt>r</dt>
<dd>Integer, number of clusters.</dd>
<dt>kappa</dt>
<dd>Positive real. A parameter of the NRMI process.</dd>
<dt>a</dt>
<dd>Positive real. Total mass of the centering measure.</dd>
<dt>delta</dt>
<dd>Scale of the Metropolis-Hastings proposal distribution</dd></dl>

Arguments

Metropolis-Hastings ratio for the conditional of logU — logacceptance_ratio_logu

<dl>

<dt>logu</dt>
<dd>Real, log of the latent variable U at the current iteration.</dd>


<dt>logu_prime</dt>
<dd>Real, log of the new proposed latent variable U.</dd>


<dt>n</dt>
<dd>Integer, number of data points.</dd>


<dt>r</dt>
<dd>Integer, number of clusters.</dd>


<dt>kappa</dt>
<dd>Positive real. A parameter of the NRMI process.</dd>


<dt>a</dt>
<dd>Positive real. Total mass of the centering measure.</dd>


<dt>delta</dt>
<dd>Scale of the Metropolis-Hastings proposal distribution</dd>

</dl>

logacceptance_ratio_logu: Metropolis-Hastings ratio for the conditional of logU

Description

Usage

Arguments