get_omega_eigens

<code>get_omega_eigens</code> calculates the eigenvalues of the "Omega" error
 term covariance matrices for each regime

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

get_omega_eigens function

<dl><dt>stvar</dt>
<dd>object of class <code>"stvar"</code></dd></dl>

Arguments

Calculate the eigenvalues of the "Omega" error term covariance matrices — get_omega_eigens

<dl>

<dt>stvar</dt>
<dd>object of class <code>"stvar"</code></dd>

</dl>

get_omega_eigens: Calculate the eigenvalues of the "Omega" error term covariance matrices

Description

Usage

Value

Arguments

References