get_boldA_eigens

<code>get_boldA_eigens</code> calculates absolute values of the eigenvalues of
 the "bold A" matrices containing the AR coefficients for each regime.

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

get_boldA_eigens function

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

Arguments

Calculate absolute values of the eigenvalues of the "bold A" matrices containing the AR coefficients — get_boldA_eigens

<dl>

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

</dl>

get_boldA_eigens: Calculate absolute values of the eigenvalues of the "bold A" matrices containing the AR coefficients

Description

Usage

Value

Arguments

References