blockcpd: Change Point Detection for Multiple Aligned Independent Time Series

Implementation of statistical models based on regularized likelihood for offline change point detection on multiple aligned independent time series. It detects changes in parameters for the specified family for the series as group or block. As a reference for the method, see Prates et al. (2021) <arXiv:2111.10187>.

Version: 1.0.0
Imports: Rcpp, graphics, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-08-12
Author: Lucas Prates ORCID iD [aut, cre], Florencia Leonardi ORCID iD [aut]
Maintainer: Lucas Prates <lucasdelprates at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: blockcpd results

Documentation:

Reference manual: blockcpd.pdf
Vignettes: blockcpd_simulation_vign

Downloads:

Package source: blockcpd_1.0.0.tar.gz
Windows binaries: r-devel: blockcpd_1.0.0.zip, r-release: blockcpd_1.0.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

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