mkhmmvb

This function creates an instance of "HMMVB" class. The function is called inside 
C code during HMMVB model training. It is not meant to be called by users.

internal

Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <https://jmlr.org/papers/v18/16-342.html>.

Jia Li

HDclust

Clustering High Dimensional Data with Hidden Markov Model on
Variable Blocks

Yevhen Tupikov

Lin Lin

Lixiang Zhang

mkhmmvb function

<dl><dt>VbStructure</dt>
<dd>An object of class 'VB' that contains variable block structure.</dd>
<dt>HmmChain</dt>
<dd>A list of objects of class 'HMM' with trained Hidden Markov Models
for each variable block.</dd>
<dt>BIC</dt>
<dd>BIC value for provided variable block structure or optimal BIC value
for found variable block structure.</dd>
<dt>diagCov</dt>
<dd>A logical value indicating whether or not covariance matrices 
for mixture models are diagonal.</dd>
<dt>Loglikehd</dt>
<dd>Loglikelihood value for each data point</dd></dl>

Arguments

Make an instance of "HMMVB" class. — mkhmmvb

<dl>

<dt>VbStructure</dt>
<dd>An object of class 'VB' that contains variable block structure.</dd>


<dt>HmmChain</dt>
<dd>A list of objects of class 'HMM' with trained Hidden Markov Models
for each variable block.</dd>


<dt>BIC</dt>
<dd>BIC value for provided variable block structure or optimal BIC value
for found variable block structure.</dd>


<dt>diagCov</dt>
<dd>A logical value indicating whether or not covariance matrices 
for mixture models are diagonal.</dd>


<dt>Loglikehd</dt>
<dd>Loglikelihood value for each data point</dd>

</dl>

mkhmmvb: Make an instance of "HMMVB" class.

Description

Usage

Value

Arguments