Package: lookout
Type: Package
Title: Leave One Out Kernel Density Estimates for Outlier Detection
Version: 2.0.0
Authors@R: c(
  person("Sevvandi", "Kandanaarachchi", email = "sevvandik@gmail.com",
  role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-0395")),
  person("Rob", "Hyndman", email = "rob.hyndman@monash.edu",
  role = c("aut"), comment = c(ORCID = "0000-0002-2140-5352")),
  person("Chris", "Fraley", role = "ctb", email = "fraley@u.washington.edu")
 )
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>
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.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
BugReports: https://github.com/sevvandi/lookout/issues
Imports: evd, ggplot2, RANN, robustbase, stats, TDAstats, tidyr
Suggests: knitr, rmarkdown
URL: https://sevvandi.github.io/lookout/,
        https://github.com/sevvandi/lookout
NeedsCompilation: no
Packaged: 2026-01-19 01:20:37 UTC; hyndman
Author: Sevvandi Kandanaarachchi [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-0337-0395>),
  Rob Hyndman [aut] (ORCID: <https://orcid.org/0000-0002-2140-5352>),
  Chris Fraley [ctb]
Repository: CRAN
Date/Publication: 2026-01-19 06:50:25 UTC
Built: R 4.5.2; ; 2026-02-15 04:32:57 UTC; windows
