calculate_sigma2maxmodel

Sigma2 is the sum of the squared errors, divided by NT. We need the sigma2 of the maxmodel to use (in term 2,3,4 of the PIC) instead of the configuration-dependent sigma2. (See paper AndoBai 2016).
sigma2_max_model could actually be set to 1 as well, as it can be absorbed in parameter C of the PIC.

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

calculate_sigma2maxmodel function

<dl><dt>e</dt>
<dd>NxT-matrix containing the estimated error term</dd>
<dt>kg_max</dt>
<dd>scalar: maximum allowed number of estimated factors for any group</dd>
<dt>S</dt>
<dd>estimated number of groups</dd>
<dt>S_cand</dt>
<dd>vector with candidate values for the number of groups</dd>
<dt>kg</dt>
<dd>vector with the estimated number of group specific factors for each group</dd>
<dt>k</dt>
<dd>estimated number of common factors</dd>
<dt>k_cand</dt>
<dd>vector with candidate value for the number of common factors</dd></dl>

Arguments

Calculates sigma2maxmodel — calculate_sigma2maxmodel

<dl>

<dt>e</dt>
<dd>NxT-matrix containing the estimated error term</dd>


<dt>kg_max</dt>
<dd>scalar: maximum allowed number of estimated factors for any group</dd>


<dt>S</dt>
<dd>estimated number of groups</dd>


<dt>S_cand</dt>
<dd>vector with candidate values for the number of groups</dd>


<dt>kg</dt>
<dd>vector with the estimated number of group specific factors for each group</dd>


<dt>k</dt>
<dd>estimated number of common factors</dd>


<dt>k_cand</dt>
<dd>vector with candidate value for the number of common factors</dd>

</dl>

calculate_sigma2maxmodel: Calculates sigma2maxmodel

Description

Usage

Value

Arguments