order_B

<code>order_B</code> takes a square matrix <code>B</code> as input and reorders its columns
so that the diagonal entries of <code>B</code> are in decreasing order. The function
is designed to be computationally efficient and ensures that the input is a square matrix.

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, counterfactual analysis, and
computation of impulse response functions, generalized impulse response functions,
generalized forecast error variance decompositions, as well as historical
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

order_B function

<dl><dt>B</dt>
<dd>A square numeric matrix.</dd></dl>

Arguments

Reorder columns of a square matrix so that the first nonzero elements are
 in decreasing order — order_B

<dl>

<dt>B</dt>
<dd>A square numeric matrix.</dd>

</dl>

order_B: Reorder columns of a square matrix so that the first nonzero elements are in decreasing order

Description

Usage

Value

Arguments