vardet

Determinant selector for chosen covariance matrix.

internal

Provides sampling and density functions for matrix
variate normal, t, and inverted t distributions; ML estimation for matrix
variate normal and t distributions using the EM algorithm,
including some restrictions on the parameters; and classification by linear and
quadratic discriminant analysis for matrix variate normal and t
distributions described in Thompson et al. (2019) <doi:10.1080/10618600.2019.1696208>.
Performs clustering with matrix variate normal and t mixture models.

Geoffrey Thompson

MixMatrix

Classification with Matrix Variate Normal and t Distributions

B. D. Ripley

W. N. Venables

vardet function

<dl><dt>n</dt>
<dd>dimensions</dd>
<dt>rho</dt>
<dd>off-diagonal parameter</dd>
<dt>deriv</dt>
<dd>logical whether to return the determinant or the derivative of
the log of the determinant</dd>
<dt>variance</dt>
<dd>variance structure - AR(1) or CS.</dd></dl>

Arguments

Determinant selector for chosen covariance matrix. — vardet

<dl>

<dt>n</dt>
<dd>dimensions</dd>


<dt>rho</dt>
<dd>off-diagonal parameter</dd>


<dt>deriv</dt>
<dd>logical whether to return the determinant or the derivative of
the log of the determinant</dd>


<dt>variance</dt>
<dd>variance structure - AR(1) or CS.</dd>

</dl>

vardet: Determinant selector for chosen covariance matrix.

Description

Usage

Value

Arguments