lookout: Leave One Out Kernel Density Estimates for Outlier Detection (original) (raw)

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.

Version: 0.1.4
Imports: TDAstats, evd, RANN, ggplot2, tidyr
Suggests: knitr, rmarkdown
Published: 2022-10-14
DOI: 10.32614/CRAN.package.lookout
Author: Sevvandi KandanaarachchiORCID iD [aut, cre], Rob Hyndman ORCID iD [aut], Chris Fraley [ctb]
Maintainer: Sevvandi Kandanaarachchi
License: GPL-3
URL: https://sevvandi.github.io/lookout/
NeedsCompilation: no
Materials: README
CRAN checks: lookout results

Documentation:

Downloads:

Reverse dependencies:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=lookoutto link to this page.