create_Fi_matrix

<code>create_Fi_matrix</code> function generates a \((T_obs \times T_obs)\) matrix
with 1's on the <code>(i+1)</code>-th sub-diagonal and 0's elsewhere.

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

create_Fi_matrix function

<dl><dt>i</dt>
<dd>Integer, the lag for which the matrix is constructed, corresponding to the sub-diagonal filled with 1's.</dd>
<dt>T_obs</dt>
<dd>Integer, the number of time periods or observations in the dataset, corresponding to the dimensions of the matrix.</dd></dl>

Arguments

Create Matrix F_i — create_Fi_matrix

<dl>

<dt>i</dt>
<dd>Integer, the lag for which the matrix is constructed, corresponding to the sub-diagonal filled with 1's.</dd>


<dt>T_obs</dt>
<dd>Integer, the number of time periods or observations in the dataset, corresponding to the dimensions of the matrix.</dd>

</dl>

create_Fi_matrix: Create Matrix F_i

Description

Usage

Value

Arguments

Details

References