postK

A Gibbs sampler algorithm was developed to estimate change points in constant-wise data sequences while performing clustering simultaneously. The algorithm is described in da Cruz, A. C. and de Souza, C. P. E "A Bayesian Approach for Clustering Constant-wise Change-point Data" <doi:10.48550/arXiv.2305.17631>.

Ana Carolina da Cruz

BayesCPclust

A Bayesian Approach for Clustering Constant-Wise Change-Point
Data

postK function

<dl><dt>kstar</dt>
<dd>A scalar with the number maximum of change points in all clusters</dd>
<dt>w</dt>
<dd>A scalar representing the minimum number of points in each interval between two change points</dd>
<dt>M</dt>
<dd>A scalar representing the number of points available for each data sequence</dd>
<dt>Y</dt>
<dd>A matrix M x N with the data sequences</dd>
<dt>cluster</dt>
<dd>A vector containing the cluster assignments for the data sequences (or its initial values)</dd>
<dt>sigma2</dt>
<dd>A vector with the variances of the data sequences (or its initial values)</dd>
<dt>lambda</dt>
<dd>A scalar defining the parameter for the Truncate Poisson distribution
that controls the number of change points (or its initial values)</dd>
<dt>clusteri</dt>
<dd>A scalar with the index of a cluster</dd></dl>

Arguments

Marginal probability of K — postK

<dl>

<dt>kstar</dt>
<dd>A scalar with the number maximum of change points in all clusters</dd>


<dt>w</dt>
<dd>A scalar representing the minimum number of points in each interval between two change points</dd>


<dt>M</dt>
<dd>A scalar representing the number of points available for each data sequence</dd>


<dt>Y</dt>
<dd>A matrix M x N with the data sequences</dd>


<dt>cluster</dt>
<dd>A vector containing the cluster assignments for the data sequences (or its initial values)</dd>


<dt>sigma2</dt>
<dd>A vector with the variances of the data sequences (or its initial values)</dd>


<dt>lambda</dt>
<dd>A scalar defining the parameter for the Truncate Poisson distribution
that controls the number of change points (or its initial values)</dd>


<dt>clusteri</dt>
<dd>A scalar with the index of a cluster</dd>

</dl>

postK: Marginal probability of K

Description

Usage

Value

Arguments

See Also

Examples