dinvWishart

Density of inverse Wishart random matrix

Kernel smoothing for Wishart random matrices described in Daayeb, Khardani and Ouimet (2025) <doi:10.48550/arXiv.2506.08816>, Gaussian and log-Gaussian models using least square or likelihood cross validation criteria for optimal bandwidth selection.

Leo Belzile

Kernel Density Estimation for Random Symmetric Positive Definite
Matrices

Frederic Ouimet

dinvWishart function

<dl><dt>x</dt>
<dd>array of dimension <code>d</code> by <code>d</code> by <code>n</code></dd>
<dt>df</dt>
<dd>degrees of freedom</dd>
<dt>S</dt>
<dd>symmetric positive definite matrix of dimension <code>d</code> by <code>d</code></dd>
<dt>log</dt>
<dd>logical; if <code>TRUE</code>, returns the log density</dd></dl>

Arguments

Density of inverse Wishart random matrix — dinvWishart

<dl>

<dt>x</dt>
<dd>array of dimension <code>d</code> by <code>d</code> by <code>n</code></dd>


<dt>df</dt>
<dd>degrees of freedom</dd>


<dt>S</dt>
<dd>symmetric positive definite matrix of dimension <code>d</code> by <code>d</code></dd>


<dt>log</dt>
<dd>logical; if <code>TRUE</code>, returns the log density</dd>

</dl>

dinvWishart: Density of inverse Wishart random matrix

Description

Usage

Value

Arguments