dots

<p>A matrix whose columns are the <code>Z</code> and <code>W</code> <code>dots</code> datasets from
Wilkinson (2016).</p>

datasets

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.

Chris Fraley interim

HDoutliers

Leland Wilkinson's Algorithm for Detecting Multidimensional
Outliers

Chris Fraley

Leland Wilkinson

dots function

One dimensional dots dataset --- outlier detection example — dots

One dimensional dots dataset --- outlier detection example

dots: One dimensional dots dataset --- outlier detection example

Description

Usage

Arguments

References