dataTrans: Data Transformation for Leland Wilkinson's _hdoutliers_...

In HDoutliers: Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers

Description

Transforms the data according to the specifications in Wilkinson's hdoutliers algorithm.

Usage

dataTrans(data) 

Arguments

data	A vector, matrix, or data frame consisting of numeric and/or categorical variables.

Details

Replaces each categorical variables with a numeric variable corresponding to its first component in multiple correspondence analysis, then maps the data to the unit square. There is no porvision for handling missing data. Functions HDoutliers and getHDoutliers apply this transformation to their input data.

Value

The transformed data, according to Wilkinson's specifications for the hdoutliers algorithm.

References

Wilkinson, L. (2016). Visualizing Outliers.

See Also

HDoutliers, getHDoutliers

Examples

 require(FactoMineR)
 data(tea)
 head(tea)
 dataTrans(tea[,-1])

HDoutliers documentation built on Feb. 11, 2022, 5:10 p.m.