print.stvarsum

<code>print.stvarsum</code> is a print method for object <code>'stvarsum'</code> generated
 by <code>summary.stvar</code>.

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

print.stvarsum function

<dl><dt>x</dt>
<dd>object of class 'stvarsum' generated by <code>summary.stvar</code>.</dd>
<dt>...</dt>
<dd>currently not used.</dd>
<dt>digits</dt>
<dd>the number of digits to be printed.</dd>
<dt>standard_error_print</dt>
<dd>if set to <code>TRUE</code>, instead of printing the estimates,
prints the approximate standard errors using square roots of the diagonal of inverse
of the observed information matrix.</dd></dl>

Arguments

Summary print method from objects of class 'stvarsum' — print.stvarsum

<dl>

<dt>x</dt>
<dd>object of class 'stvarsum' generated by <code>summary.stvar</code>.</dd>


<dt>...</dt>
<dd>currently not used.</dd>


<dt>digits</dt>
<dd>the number of digits to be printed.</dd>


<dt>standard_error_print</dt>
<dd>if set to <code>TRUE</code>, instead of printing the estimates,
prints the approximate standard errors using square roots of the diagonal of inverse
of the observed information matrix.</dd>

</dl>

print.stvarsum: Summary print method from objects of class 'stvarsum'

Description

Usage

Value

Arguments