beta_true_heterogroups

Helpfunction in create_true_beta() for the option beta_true_heterogeneous_groups. (This is the default option.)

Robust Clustering of Time Series (RCTS) has the functionality to cluster time series using both the classical and the robust interactive fixed effects framework.
The classical framework is developed in Ando & Bai (2017) <doi:10.1080/01621459.2016.1195743>. The implementation within this package excludes the SCAD-penalty on the estimations of beta.
This robust framework is developed in Boudt & Heyndels (2022) <doi:10.1016/j.ecosta.2022.01.002> and is made robust against different kinds of outliers.
The algorithm iteratively updates beta (the coefficients of the observable variables), group membership, and the latent factors (which can be common and/or group-specific) along
with their loadings. The number of groups and factors can be estimated if they are unknown.

Ewoud Heyndels

RCTS

Clustering Time Series While Resisting Outliers

beta_true_heterogroups function

<dl><dt>vars</dt>
<dd>number of observable variables</dd>
<dt>S_true</dt>
<dd>true number of groups: should be at least 1 and maximum limit_true_groups</dd>
<dt>extra_beta_factor</dt>
<dd>option to multiply the coefficients in true beta; default = 1</dd>
<dt>limit_true_groups</dt>
<dd>Maximum number of true groups in a simulation-DGP for which the code in this package is implemented. Currently equals 12. For application on realworld data this parameter is not relevant.</dd></dl>

Arguments

Helpfunction in create_true_beta() for the option beta_true_heterogeneous_groups. (This is the default option.) — beta_true_heterogroups

<dl>

<dt>vars</dt>
<dd>number of observable variables</dd>


<dt>S_true</dt>
<dd>true number of groups: should be at least 1 and maximum limit_true_groups</dd>


<dt>extra_beta_factor</dt>
<dd>option to multiply the coefficients in true beta; default = 1</dd>


<dt>limit_true_groups</dt>
<dd>Maximum number of true groups in a simulation-DGP for which the code in this package is implemented. Currently equals 12. For application on realworld data this parameter is not relevant.</dd>

</dl>

beta_true_heterogroups: Helpfunction in create_true_beta() for the option beta_true_heterogeneous_groups. (This is the default option.)

Description

Usage

Value

Arguments