dlogmultistudent

<code>dlogmultistudent</code> calculates logarithms of multiple multivariate
 Student's t densities with varying mean and covaraince matrix of specific structure.

internal

Unconstrained and constrained maximum likelihood estimation of structural and reduced form
Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t
mixture vector autoregressive models, quantile residual tests, graphical diagnostics,
simulations, forecasting, and estimation of generalized impulse response function and generalized
forecast error variance decomposition.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>,
Savi Virolainen (2025) <doi:10.1080/07350015.2024.2322090>,
Savi Virolainen (2022) <doi:10.48550/arXiv.2109.13648>.

Savi Virolainen

gmvarkit

Estimate Gaussian and Student's t Mixture Vector Autoregressive
Models

dlogmultistudent function

<dl><dt>y</dt>
<dd>dimension \((T x k)\) matrix where each row is a k-dimensional vector</dd>
<dt>mu</dt>
<dd>dimension \((T x k)\) matrix where each row is the mean of the k-dimensional
vector in corresponding row of <code>y</code>.</dd>
<dt>inv_Omega</dt>
<dd>inverse of the \((k x k)\) covariance matrix Omega.</dd>
<dt>log_det_Omega</dt>
<dd>logarithm of the determinant of the covariance matrix Omega.</dd>
<dt>arch_scalars</dt>
<dd>length \(T\) numeric vector containing the coefficients that multiply
the covariance matrix <code>Omega</code>.</dd>
<dt>df</dt>
<dd>the degrees of freedom parameter that is common for all \(t=1,...,T\).</dd></dl>

Arguments

Calculate logarithms of multiple multivariate Student's t densities with varying
 mean and covariance matrix of specific structure, but constant degrees of freedom. — dlogmultistudent

<dl>

<dt>y</dt>
<dd>dimension \((T x k)\) matrix where each row is a k-dimensional vector</dd>


<dt>mu</dt>
<dd>dimension \((T x k)\) matrix where each row is the mean of the k-dimensional
vector in corresponding row of <code>y</code>.</dd>


<dt>inv_Omega</dt>
<dd>inverse of the \((k x k)\) covariance matrix Omega.</dd>


<dt>log_det_Omega</dt>
<dd>logarithm of the determinant of the covariance matrix Omega.</dd>


<dt>arch_scalars</dt>
<dd>length \(T\) numeric vector containing the coefficients that multiply
the covariance matrix <code>Omega</code>.</dd>


<dt>df</dt>
<dd>the degrees of freedom parameter that is common for all \(t=1,...,T\).</dd>

</dl>

Calculate logarithms of multiple multivariate Student's t densities with varying
 mean and covariance matrix of specific structure, but constant degrees of freedom.

dlogmultistudent: Calculate logarithms of multiple multivariate Student's t densities with varying mean and covariance matrix of specific structure, but constant degrees of freedom.

Description

Usage

Value

Arguments