plotHDoutliers: Display Outlier Detection Results

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

Description

Plotting function showing observations determined to be outliers.

Usage

plotHDoutliers(data, indexes = NULL, transform = TRUE, ...) 

Arguments

data	A vector, matrix, or data frame consisting of numeric and/or categorical variables.
indexes	The (row) indexes of the outliers in data.
transform	A logical variable indicating whether or not the data needs to be transformed to conform to Wilkinson's specifications before outlier detection. The default is to transform the data using function dataTrans. In Wilksinson's algorithm, indexes would have been derived from transformed data.
...	Additional plotting arguments.

Details

Produces a plot of the data (transformed according to the Wilkinson's specifications) showing the outliers. If the data has more than two dimensions, it is plotted onto the principal components of the data that remains after removing outliers.

Value

The indexes of the observations determined to be outliers.

References

Wilkinson, L. (2016). Visualizing Outliers.

See Also

HDoutliers, dataTrans

Examples

data(dots)
out.W <- HDoutliers(dots$W)
## Not run: 
plotHDoutliers(dots$W,out.W)
## End(Not run)

data(ex2D)
out.ex2D <- HDoutliers(ex2D)
## Not run: 
plotHDoutliers(ex2D,out.ex2D)
## End(Not run)

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