get_minval

<code>get_minval</code> returns the default smallest allowed log-likelihood for given data.

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_minval function

<dl><dt>data</dt>
<dd>a matrix or class <code>'ts'</code> object with <code>d&gt;1</code> columns. Each column is taken to represent
a univariate time series. Missing values are not supported.</dd></dl>

Arguments

Returns the default smallest allowed log-likelihood for given data. — get_minval

<dl>

<dt>data</dt>
<dd>a matrix or class <code>'ts'</code> object with <code>d&gt;1</code> columns. Each column is taken to represent
a univariate time series. Missing values are not supported.</dd>

</dl>

get_minval: Returns the default smallest allowed log-likelihood for given data.

Description

Usage

Value

Arguments