CRAN/E | RCTS

RCTS

Clustering Time Series While Resisting Outliers

Installation

About

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.

Key Metrics

Version 0.2.4
R ≥ 4.1.0
Published 2023-05-18 351 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks RCTS results

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Maintainer

Maintainer

Ewoud Heyndels

ewoud.heyndels@vub.be

Authors

Ewoud Heyndels

aut / cre

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

RCTS archive

Depends

R ≥ 4.1.0

Imports

stats
magrittr
dplyr
purrr
stringr
tidyr
tibble
ggplot2
ncvreg
robustbase
cellWise
rlang
Rdpack

Suggests

tsqn
doParallel
doSNOW
foreach
mclust
Matrix