VAR_pcovmat

<code>VAR_pcovmat</code> calculate the dp-dimensional covariance matrix of p consecutive
 observations of a VAR process with the algorithm proposed by McElroy (2017).

internal

Penalized and non-penalized maximum likelihood estimation of smooth
transition vector autoregressive models with various types of transition weight
functions, conditional distributions, and identification methods. Constrained
estimation with various types of constraints is available. Residual based
model diagnostics, forecasting, simulations, and calculation of impulse
response functions, generalized impulse response functions, and generalized
forecast error variance decompositions. See
Heather Anderson, Farshid Vahid (1998) <doi:10.1016/S0304-4076(97)00076-6>,
Helmut Lütkepohl, Aleksei Netšunajev (2017) <doi:10.1016/j.jedc.2017.09.001>,
Markku Lanne, Savi Virolainen (2025) <doi:10.48550/arXiv.2403.14216>,
Savi Virolainen (2025) <doi:10.48550/arXiv.2404.19707>.

Savi Virolainen

sstvars

Toolkit for Reduced Form and Structural Smooth Transition Vector
Autoregressive Models

VAR_pcovmat function

<dl><dt>p</dt>
<dd>a positive integer specifying the autoregressive order</dd>
<dt>d</dt>
<dd>the number of time series in the system, i.e., the dimension</dd>
<dt>all_Am</dt>
<dd><code>[d, d, p]</code> array containing the AR coefficient matrices</dd>
<dt>Omega_m</dt>
<dd>the \((d\times d)\) positive definite error term covariance matrix</dd></dl>

Arguments

Calculate the dp-dimensional covariance matrix of p consecutive
 observations of a VAR process — VAR_pcovmat

<dl>

<dt>p</dt>
<dd>a positive integer specifying the autoregressive order</dd>


<dt>d</dt>
<dd>the number of time series in the system, i.e., the dimension</dd>


<dt>all_Am</dt>
<dd><code>[d, d, p]</code> array containing the AR coefficient matrices</dd>


<dt>Omega_m</dt>
<dd>the \((d\times d)\) positive definite error term covariance matrix</dd>

</dl>

VAR_pcovmat: Calculate the dp-dimensional covariance matrix of p consecutive observations of a VAR process

Description

Usage

Value

Arguments

Details

References