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.
- Version1.2
- R version≥ 3.5.0 methods
- LicenseGPL-2
- Needs compilation?Yes
- Adams and MacKay (2007)
- Wendelberger et. al. (2021)
- Last release12/13/2023
Documentation
Team
Shannon T. Holloway
Josh Gray
Show author detailsRolesAuthorLaura Wendelberger
Show author detailsRolesAuthorBrian Reich
Show author detailsRolesAuthorAlyson Wilson
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 144 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,915 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 23 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Suggests1 package
- Linking To3 packages