create_true_beta

Creates beta_true, which contains the true values of beta (= the coefficients of X)

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

create_true_beta function

<dl><dt>vars</dt>
<dd>number of observable variables</dd>
<dt>NN</dt>
<dd>number of time series</dd>
<dt>S_true</dt>
<dd>number of groups</dd>
<dt>method_true_beta</dt>
<dd>how the true values of beta are defined: "homogeneous" (equal for all individuals),
"heterogeneous_groups" (equal within groups, and different between groups) or heterogeneous_individuals (different for all individuals)</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>
<dt>extra_beta_factor</dt>
<dd>multiplies coefficients in beta_est; default = 1</dd></dl>

Arguments

Creates beta_true, which contains the true values of beta (= the coefficients of X) — create_true_beta

<dl>

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


<dt>NN</dt>
<dd>number of time series</dd>


<dt>S_true</dt>
<dd>number of groups</dd>


<dt>method_true_beta</dt>
<dd>how the true values of beta are defined: "homogeneous" (equal for all individuals),
"heterogeneous_groups" (equal within groups, and different between groups) or heterogeneous_individuals (different for all individuals)</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>


<dt>extra_beta_factor</dt>
<dd>multiplies coefficients in beta_est; default = 1</dd>

</dl>

create_true_beta: Creates beta_true, which contains the true values of beta (= the coefficients of X)

Description

Usage

Value

Arguments