unvec

<code>unvec</code> forms a square matrix from a vector of
 stacked columns, stacked by <code>vec</code>.

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

unvec function

<dl><dt>d</dt>
<dd>the number of rows in the square matrix to be formed.</dd>
<dt>a</dt>
<dd>a size \((d^2x1)\) vector to be unvectorized into a \((dxd)\) matrix.</dd></dl>

Arguments

Reverse vectorization operator — unvec

<dl>

<dt>d</dt>
<dd>the number of rows in the square matrix to be formed.</dd>


<dt>a</dt>
<dd>a size \((d^2x1)\) vector to be unvectorized into a \((dxd)\) matrix.</dd>

</dl>

unvec: Reverse vectorization operator

Description

Usage

Value

Arguments