CRAN/E | lookout

lookout

Leave One Out Kernel Density Estimates for Outlier Detection

Installation

About

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.

sevvandi.github.io/lookout/

Key Metrics

Version 0.1.4
Published 2022-10-14 567 days ago
Needs compilation? no
License GPL-3
CRAN checks lookout results

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Maintainer

Maintainer

Sevvandi Kandanaarachchi

sevvandik@gmail.com

Authors

Sevvandi Kandanaarachchi

aut / cre

Rob Hyndman

aut

Chris Fraley

ctb

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lookout archive

Imports

TDAstats
evd
RANN
ggplot2
tidyr

Suggests

knitr
rmarkdown