gammaLogLikelihood

Used in calculating model probability in Metropolis-Hastings 
algorithm when proposals are from the Gamma distribution.

Semi-supervised and unsupervised Bayesian mixture models that
simultaneously infer the cluster/class structure and a batch correction.
Densities available are the multivariate normal and the multivariate t.
The model sampler is implemented in C++. This package is aimed at analysis of
low-dimensional data generated across several batches. See Coleman et al.
(2022) <doi:10.1101/2022.01.14.476352> for details of the model.

Stephen Coleman

batchmix

Semi-Supervised Bayesian Mixture Models Incorporating Batch
Correction

Paul Kirk

Chris Wallace

gammaLogLikelihood function

<dl><dt>x</dt>
<dd>- double; the value to calculate the unnormalised likelihood of.</dd>
<dt>shape</dt>
<dd>- double; the shape of the Gamma distribution.</dd>
<dt>rate</dt>
<dd>- double; the rate of the Gamma distribution</dd></dl>

Arguments

Gamma log-likelihood — gammaLogLikelihood

<dl>

<dt>x</dt>
<dd>- double; the value to calculate the unnormalised likelihood of.</dd>


<dt>shape</dt>
<dd>- double; the shape of the Gamma distribution.</dd>


<dt>rate</dt>
<dd>- double; the rate of the Gamma distribution</dd>

</dl>

gammaLogLikelihood: Gamma log-likelihood

Description

Usage

Value

Arguments