lookout
Leave One Out Kernel Density Estimates for Outlier Detection
Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.
- Version0.1.4
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release10/14/2022
Documentation
Team
Sevvandi Kandanaarachchi
Chris Fraley
Show author detailsRolesContributorRob Hyndman
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
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
- Imports5 packages
- Suggests2 packages
- Reverse Imports1 package