The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
RCTS: Clustering Time Series While Resisting Outliers
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.
| Version: |
0.2.4 |
| 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 |
| Published: |
2023-05-18 |
| DOI: |
10.32614/CRAN.package.RCTS |
| Author: |
Ewoud Heyndels 
[aut, cre] |
| Maintainer: |
Ewoud Heyndels <ewoud.heyndels at vub.be> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
RCTS results [issues need fixing before 2025-01-12] |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=RCTS
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.