check_pMd

<code>check_pMd</code> checks the arguments p, M, and d.

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

check_pMd function

<dl><dt>p</dt>
<dd>the autoregressive order of the model</dd>
<dt>M</dt>
<dd>the number of regimes</dd>
<dt>d</dt>
<dd>the number of time series in the system, i.e., the dimension</dd></dl>

Arguments

Check that p, M, and d are correctly set — check_pMd

<dl>

<dt>p</dt>
<dd>the autoregressive order of the model</dd>


<dt>M</dt>
<dd>the number of regimes</dd>


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

</dl>

check_pMd: Check that p, M, and d are correctly set

Description

Usage

Value

Arguments