form_boldA

<code>form_boldA</code> creates the "bold A" (companien form) coefficient matrices related to
 VAR processes.

internal

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 (2024) <doi:10.48550/arXiv.2403.14216>,
Savi Virolainen (2024) <doi:10.48550/arXiv.2404.19707>.

Savi Virolainen

sstvars

Toolkit for Reduced Form and Structural Smooth Transition Vector
Autoregressive Models

form_boldA 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>
<dt>all_A</dt>
<dd>4D array containing all coefficient matrices \(A_{m,i}\), obtained from <code>pick_allA</code>.</dd></dl>

Arguments

Warning

Form the \((dp\times dp)\) "bold A" matrices related to the VAR processes — form_boldA

<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>


<dt>all_A</dt>
<dd>4D array containing all coefficient matrices \(A_{m,i}\), obtained from <code>pick_allA</code>.</dd>

</dl>

form_boldA: Form the \((dp\times dp)\) "bold A" matrices related to the VAR processes

Description

Usage

Value

Arguments

Warning

Details

References