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Leave One Out Kernel Density Estimates for Outlier Detection

v2.0.1 · Mar 26, 2026 · GPL-3

Description

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.

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (2)

imports

Dependency Network

Dependencies Reverse dependencies evd ggplot2 mlpack RANN robustbase tidyr oddnet weird lookout

Version History

updated 2.0.1 ← 2.0.0 diff Mar 26, 2026
new 2.0.0 Mar 10, 2026
updated 2.0.0 ← 0.1.4 diff Jan 18, 2026
updated 0.1.4 ← 0.1.3 diff Oct 13, 2022
updated 0.1.3 ← 0.1.2 diff Sep 29, 2022
updated 0.1.2 ← 0.1.0 diff Aug 25, 2022
new 0.1.0 Feb 11, 2021