_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-lookout 2.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tdastats@0.4.1 r-robustbase@0.99-6 r-rann@2.6.2 r-ggplot2@4.0.1 r-evd@2.3-7.1
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://sevvandi.github.io/lookout/
Licenses: GPL 3
Build system: r
Synopsis: Leave One Out Kernel Density Estimates for Outlier Detection
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.

Total results: 1