Package: lookout 2.0.1.00

Sevvandi Kandanaarachchi

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.

Authors:Sevvandi Kandanaarachchi [aut, cre], Rob Hyndman [aut], Chris Fraley [ctb]

lookout_2.0.1.00.tar.gz
lookout_2.0.1.00.zip(r-4.7)lookout_2.0.1.00.zip(r-4.6)lookout_2.0.1.00.zip(r-4.5)
lookout_2.0.1.00.tgz(r-4.6-any)lookout_2.0.1.00.tgz(r-4.5-any)
lookout_2.0.1.00.tar.gz(r-4.7-any)lookout_2.0.1.00.tar.gz(r-4.6-any)
lookout_2.0.1.00.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
lookout/json (API)
NEWS

# Install 'lookout' in R:
install.packages('lookout', repos = c('https://sevvandi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sevvandi/lookout/issues

Pkgdown/docs site:https://sevvandi.github.io

On CRAN:

Conda:

5.48 score 29 stars 1 packages 10 scripts 622 downloads 6 exports 37 dependencies

Last updated from:caba04b4c2. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK152
source / vignettesOK229
linux-release-x86_64OK147
macos-release-arm64OK102
macos-oldrel-arm64OK99
windows-develOK135
windows-releaseOK99
windows-oldrelOK90
wasm-releaseOK113

Exports:autoplotfind_tda_bwlookoutlookout_tsmvscalepersisting_outliers

Dependencies:clicpp11DEoptimRdplyrevdfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrmlpackpillarpkgconfigpurrrR6RANNRColorBrewerRcppRcppArmadilloRcppEnsmallenrlangrobustbaseS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr