PlotMD: QQ-Plot of Mahalanobis distances

In modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data

QQ-Plot of Mahalanobis distances

Description

QQ-plot of (squared) Mahalanobis distances vs. scaled F-distribution (or a scaled chisquare distribution). In addition, two default cutpoints are proposed.

Usage

PlotMD(dist, p, alpha = 0.95, chisquare = FALSE)

Arguments

dist	a vector of Mahalanobis distances.
p	the number of variables involved in the Mahalanobis distances.
alpha	a probability for cut-off, usually close to 1.
chisquare	a logical indicating the the chisquare distribution should be used instead of the F-distribution.

Details

Scaling of the F-distribution as median(dist)*qf((1:n)/(n+1), p, n-p)/qf(0.5, p, n-p). First default cutpoint is median(dist)*qf(alpha, p, n-p)/qf(0.5, p, n-p) and the second default cutpoint is the alpha quantile of the Mahalanobis distances.

Value

hmed	first proposed cutpoint based on F-distribution
halpha	second proposed cutpoint (alpha-quantile)
QQ-plot

Author(s)

Beat Hulliger

References

Little, R. & Smith, P. (1987) Editing and imputation for quantitative survey data, Journal of the American Statistical Association, 82, 58-68

Examples

data(bushfirem, bushfire.weights)
det.res <- TRC(bushfirem, weights = bushfire.weights)
PlotMD(det.res$dist, ncol(bushfirem))

modi documentation built on March 31, 2023, 8:35 p.m.