Package: bayesWatch
Type: Package
Title: Bayesian Change-Point Detection for Process Monitoring with
        Fault Detection
Version: 0.1.4
Authors@R: c(
    person("Alexander C.", "Murph",
           email = "murph290@gmail.com",
           role = c("aut", "cre")),
    person("Reza", "Mohammadi",
           role = c("ctb", "cph")),
    person("Alex", "Lenkoski",
           role = c("ctb", "cph")),
    person("Andrew", "Johnson",
           role = "ctb"))
Maintainer: Alexander C. Murph <murph290@gmail.com>
Description: Bayes Watch fits an array of Gaussian Graphical Mixture Models to groupings of homogeneous data in time, called regimes, which are modeled as the observed states of a Markov process with unknown transition probabilities.  In doing so, Bayes Watch defines a posterior distribution on a vector of regime assignments, which gives meaningful expressions on the probability of every possible change-point.  Bayes Watch also allows for an effective and efficient fault detection system that assesses what features in the data where the most responsible for a given change-point.  For further details, see: Alexander C. Murph et al. (2023) <doi:10.48550/arXiv.2310.02940>.
Copyright: file COPYRIGHTS
License: GPL-3
Imports: Rcpp (>= 1.0.7), parallel (>= 3.6.2), Matrix, Hotelling,
        CholWishart, ggplot2, gridExtra (>= 0.9.1), BDgraph, methods,
        MASS, stats, ess
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, Matrix, CholWishart, BH
Depends: R (>= 3.5.0)
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: yes
Packaged: 2025-08-30 20:04:31 UTC; root
Repository: CRAN
Date/Publication: 2025-08-30 20:20:02 UTC
Author: Alexander C. Murph [aut, cre],
  Reza Mohammadi [ctb, cph],
  Alex Lenkoski [ctb, cph],
  Andrew Johnson [ctb]
Built: R 4.4.3; x86_64-w64-mingw32; 2026-01-21 04:10:40 UTC; windows
Archs: x64
