random_impactmat

<code>random_impactmat</code> generates random VAR model $(dxd)$ impact matrix $B$
 with its elements drawn from specific normal distributions (see the source code). If not the first
 regime, will create the matrix $B_m*$.

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

random_impactmat function

<dl><dt>B_scale</dt>
<dd>a size $(d \times 1)$ strictly positive vector specifying the mean and variability of the
random impact matrices in random mutations. In Regime 1, the mean of the error term covariance matrix
implied by the random impact matrix will be <code>0.95*diag(B_scale)</code> and in the rest of the regimes <code>diag(B_scale)</code>,
whereas the variability increases with <code>B_scale</code>.
Default in <code>GAfit</code> is <code>var(stats::ar(data[,i], order.max=10)$resid, na.rm=TRUE), i=1,...,d</code>.
This argument is ignored if <code>cond_dist != "ind_Student"</code>.</dd>
<dt>is_regime1</dt>
<dd>is the impact matrix for Regime 1? Regime 1 impact matrix is constrained so the elements
in its first row are in a decreasing ordering and the diagonal elements are strictly positive.</dd></dl>

Arguments

Create random VAR model impact matrix — random_impactmat

<dl>

<dt>B_scale</dt>
<dd>a size $(d \times 1)$ strictly positive vector specifying the mean and variability of the
random impact matrices in random mutations. In Regime 1, the mean of the error term covariance matrix
implied by the random impact matrix will be <code>0.95*diag(B_scale)</code> and in the rest of the regimes <code>diag(B_scale)</code>,
whereas the variability increases with <code>B_scale</code>.
Default in <code>GAfit</code> is <code>var(stats::ar(data[,i], order.max=10)$resid, na.rm=TRUE), i=1,...,d</code>.
This argument is ignored if <code>cond_dist != "ind_Student"</code>.</dd>


<dt>is_regime1</dt>
<dd>is the impact matrix for Regime 1? Regime 1 impact matrix is constrained so the elements
in its first row are in a decreasing ordering and the diagonal elements are strictly positive.</dd>

</dl>

random_impactmat: Create random VAR model impact matrix

Description

Usage

Value

Arguments

Details