Package: roboBayes
Type: Package
Title: Robust Online Bayesian Monitoring
Version: 1.1
Date: 2022-08-11
Authors@R: c(person("Laura", "Wendelberger", role = "aut"),
             person("Josh", "Gray", role = "aut"),
             person("Brian", "Reich", role = "aut"),
             person("Alyson", "Wilson", role = "aut"),
             person("Shannon T.", "Holloway", role = c("aut", "cre"),
                     email = "shannon.t.holloway@gmail.com"))
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@gmail.com>
Description: An implementation of Bayesian online changepoint detection (Adams and MacKay (2007) <arXiv:0710.3742>) with an option for probability based outlier detection and removal (Wendelberger et. al. (2021) <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.
License: GPL-2
Depends: R (>= 3.5.0), methods
Imports: Rcpp (>= 1.0.7)
Suggests: mvtnorm
NeedsCompilation: yes
LinkingTo: Rcpp, RcppArmadillo, RcppDist
Repository: CRAN
Encoding: UTF-8
RoxygenNote: 7.2.1
Collate: 'RcppExports.R' 'checkTypes.R' 'regressionInit.R'
        'initRoboBayes.R' 'verifyAnalysisSettings.R' 'roboBayes.R'
Packaged: 2022-08-15 12:06:27 UTC; 19194
Date/Publication: 2022-08-16 10:00:02 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 15:17:19 UTC; windows
Archs: i386, x64
