rmnorm

Sampler derived using the eigendecomposition of the covariance
matrix <code>vcov</code>.

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

rmnorm function

<dl><dt>n</dt>
<dd>sample size</dd>
<dt>mean</dt>
<dd>mean vector of length <code>d</code></dd>
<dt>vcov</dt>
<dd>a square positive definite covariance matrix, of the same dimension as <code>mean</code>.</dd></dl>

Arguments

Random vector generation from the multivariate normal distribution — rmnorm

<dl>

<dt>n</dt>
<dd>sample size</dd>


<dt>mean</dt>
<dd>mean vector of length <code>d</code></dd>


<dt>vcov</dt>
<dd>a square positive definite covariance matrix, of the same dimension as <code>mean</code>.</dd>

</dl>

rmnorm: Random vector generation from the multivariate normal distribution

Description

Usage

Value

Arguments

Examples