movMF_reduce_greedy

When given parameters of the von Mises-Fisher mixture model, this function 
aims at mixture model reduction using a greedy method.

Matrix is an universal and sometimes primary object/unit in applied mathematics and statistics. We provide a number of algorithms for selected problems in optimization and statistical inference. For general exposition to the topic with focus on statistical context, see the book by Banerjee and Roy (2014, ISBN:9781420095388).

Kisung You

maotai

Tools for Matrix Algebra, Optimization and Inference

movMF_reduce_greedy function

<dl><dt>means</dt>
<dd>a \((K \times p)\) matrix of means of the von Mises-Fisher components.</dd>
<dt>concentrations</dt>
<dd>a \(K\) vector of concentrations of the von Mises-Fisher components.</dd>
<dt>weights</dt>
<dd>a \(K\) vector of weights of the von Mises-Fisher components.</dd>
<dt>target.num</dt>
<dd>a desired number of components after reduction. Default is 2.</dd></dl>

Arguments

von Mises-Fisher mixture model reduction - Greedy method — movMF_reduce_greedy

<dl>

<dt>means</dt>
<dd>a \((K \times p)\) matrix of means of the von Mises-Fisher components.</dd>


<dt>concentrations</dt>
<dd>a \(K\) vector of concentrations of the von Mises-Fisher components.</dd>


<dt>weights</dt>
<dd>a \(K\) vector of weights of the von Mises-Fisher components.</dd>


<dt>target.num</dt>
<dd>a desired number of components after reduction. Default is 2.</dd>

</dl>

movMF_reduce_greedy: von Mises-Fisher mixture model reduction - Greedy method

Description

Usage

Value

Arguments