generate_Y

Generate panel data Y for simulations.

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

generate_Y function

<dl><dt>NN</dt>
<dd>number of time series</dd>
<dt>TT</dt>
<dd>length of time series</dd>
<dt>k_true</dt>
<dd>true number of common factors</dd>
<dt>kg_true</dt>
<dd>Vector of length the number of groups. Each element contains the true number of group factors for that group.</dd>
<dt>g_true</dt>
<dd>vector of length NN with true group memberships</dd>
<dt>beta_true</dt>
<dd>true coefficients of the observable variables</dd>
<dt>lambda_group_true</dt>
<dd>loadings of the true group specific factors</dd>
<dt>factor_group_true</dt>
<dd>true group specific factors</dd>
<dt>lambda_true</dt>
<dd>loadings of the true common factors</dd>
<dt>comfactor_true</dt>
<dd>true common factors</dd>
<dt>eps</dt>
<dd>NN x TT-matrix containing the error term</dd>
<dt>X</dt>
<dd>dataframe with the observed variables</dd></dl>

Arguments

Generate panel data Y for simulations. — generate_Y

<dl>

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


<dt>TT</dt>
<dd>length of time series</dd>


<dt>k_true</dt>
<dd>true number of common factors</dd>


<dt>kg_true</dt>
<dd>Vector of length the number of groups. Each element contains the true number of group factors for that group.</dd>


<dt>g_true</dt>
<dd>vector of length NN with true group memberships</dd>


<dt>beta_true</dt>
<dd>true coefficients of the observable variables</dd>


<dt>lambda_group_true</dt>
<dd>loadings of the true group specific factors</dd>


<dt>factor_group_true</dt>
<dd>true group specific factors</dd>


<dt>lambda_true</dt>
<dd>loadings of the true common factors</dd>


<dt>comfactor_true</dt>
<dd>true common factors</dd>


<dt>eps</dt>
<dd>NN x TT-matrix containing the error term</dd>


<dt>X</dt>
<dd>dataframe with the observed variables</dd>

</dl>

generate_Y: Generate panel data Y for simulations.

Description

Usage

Value

Arguments