HDoutliers: Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers
Version 0.15

An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers. See .

Getting started

Package details

AuthorChris Fraley [aut, cre], Leland Wilkinson [ctb]
Date of publication2016-12-24 11:23:58
MaintainerChris Fraley <cfraley@tableau.com>
LicenseMIT + file LICENSE
Version0.15
URL https://www.r-project.org https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("HDoutliers")

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HDoutliers documentation built on May 30, 2017, 6:25 a.m.