reassign_if_empty_groups

Randomly reassign individual(s) if there are empty groups. This can happen if the total number of time series is low compared to the number of desired groups.

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

reassign_if_empty_groups function

<dl><dt>g</dt>
<dd>Vector with group membership for all individuals</dd>
<dt>S_true</dt>
<dd>true number of groups</dd>
<dt>NN</dt>
<dd>number of time series</dd></dl>

Arguments

Randomly reassign individual(s) if there are empty groups. This can happen if the total number of time series is low compared to the number of desired groups. — reassign_if_empty_groups

<dl>

<dt>g</dt>
<dd>Vector with group membership for all individuals</dd>


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


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

</dl>

Randomly reassign individual(s) if there are empty groups. This can happen if the total number of time series is low compared to the number of desired groups.

reassign_if_empty_groups: Randomly reassign individual(s) if there are empty groups. This can happen if the total number of time series is low compared to the number of desired groups.

Description

Usage

Value

Arguments