summary.NetVAR

<code>summary.NetVAR</code> prints the values of an object of class NetVAR.

Vector AutoRegressive (VAR) type models with tailored regularisation structures are provided to uncover network type structures in the data, such as influential time series (influencers). Currently the package implements the LISAR model from Zhang and Trimborn (2023) <doi:10.2139/ssrn.4619531>. The package automatically derives the required regularisation sequences and refines it during the estimation to provide the optimal model. The package allows for model optimisation under various loss functions such as Mean Squared Forecasting Error (MSFE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). It provides a dedicated class, allowing for summary prints of the optimal model and a plotting function to conveniently analyse the optimal model via heatmaps.

Simon Trimborn

NetVAR

Network Structures in VAR Models

summary.NetVAR function

<dl><dt>object</dt>
<dd>An object of <code>class</code> NetVAR</dd>
<dt>...</dt>
<dd>Further arguments to be passed over. Currently none.</dd></dl>

Arguments

Printing function for objects of class NetVAR — summary.NetVAR

<dl>

<dt>object</dt>
<dd>An object of <code>class</code> NetVAR</dd>


<dt>...</dt>
<dd>Further arguments to be passed over. Currently none.</dd>

</dl>

summary.NetVAR: Printing function for objects of class NetVAR

Description

Usage

Value

Arguments