roboBayes: Robust Online Bayesian Monitoring

An implementation of Bayesian online changepoint detection (Adams and MacKay (2007) <doi:10.48550/arXiv.0710.3742>) with an option for probability based outlier detection and removal (Wendelberger et. al. (2021) <doi:10.48550/arXiv.2112.12899>). Building on the independent multivariate constant mean model implemented in the 'R' package 'ocp', this package models multivariate data as multivariate normal about a linear trend, defined by user input covariates, with an unstructured error covariance. Changepoints are identified based on a probability threshold for windows of points.

Version: 1.2
Depends: R (≥ 3.5.0), methods
Imports: Rcpp (≥ 1.0.7), RcppArmadillo
LinkingTo: Rcpp, RcppArmadillo, RcppDist
Suggests: mvtnorm
Published: 2023-12-13
DOI: 10.32614/CRAN.package.roboBayes
Author: Laura Wendelberger [aut], Josh Gray [aut], Brian Reich [aut], Alyson Wilson [aut], Shannon T. Holloway [aut, cre]
Maintainer: Shannon T. Holloway <shannon.t.holloway at>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
CRAN checks: roboBayes results


Reference manual: roboBayes.pdf


Package source: roboBayes_1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): roboBayes_1.2.tgz, r-oldrel (arm64): roboBayes_1.2.tgz, r-release (x86_64): roboBayes_1.2.tgz, r-oldrel (x86_64): roboBayes_1.2.tgz
Old sources: roboBayes archive


Please use the canonical form to link to this page.