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.


Reference manual

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0.1.0 by Sevvandi Kandanaarachchi, a year ago


Browse source code at https://github.com/cran/lookout

Authors: Sevvandi Kandanaarachchi [aut, cre] , Rob Hyndman [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports TDAstats, evd, RANN, ggplot2, tidyr

Suggests knitr, rmarkdown

See at CRAN