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bayesWatch  

Bayesian Change-Point Detection for Process Monitoring with Fault Detection
View on CRAN: Click here


Download and install bayesWatch package within the R console
Install from CRAN:
install.packages("bayesWatch")

Install from Github:
library("remotes")
install_github("cran/bayesWatch")

Install by package version:
library("remotes")
install_version("bayesWatch", "0.1.4")



Attach the package and use:
library("bayesWatch")
Maintained by
Alexander C. Murph
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-10-23
Latest Update: 2024-01-27
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) .
How to cite:
Alexander C. Murph (2023). bayesWatch: Bayesian Change-Point Detection for Process Monitoring with Fault Detection. R package version 0.1.4, https://cran.r-project.org/web/packages/bayesWatch. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.0 (2023-10-23 18:20), 0.1.1 (2023-11-05 07:30), 0.1.2 (2023-11-20 20:10), 0.1.3 (2024-01-27 18:50)
Other packages that cited bayesWatch R package
View bayesWatch citation profile
Other R packages that bayesWatch depends, imports, suggests or enhances
Complete documentation for bayesWatch
Functions, R codes and Examples using the bayesWatch R package
Some associated functions: bayeswatch . detect_faults . full_data . get_point_estimate . plot.bayesWatch . print.bayesWatch . 
Some associated R codes: RcppExports.R . create_simulated_data.R . fit_regimes.R . helpers.R . posterior_analysis.R . simulated_data.R .  Full bayesWatch package functions and examples
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