Hawkins, Bradu, Kass's Artificial Data
Artificial Data Set generated by Hawkins, Bradu, and Kass (1984). The
data set consists of 75 observations in four dimensions (one response
and three explanatory variables). It provides a good example of the
masking effect. The first 14 observations are outliers, created in
two groups: 1–10 and 11–14.
Only observations 12, 13 and 14 appear as outliers when using
classical methods, but can be easily unmasked using robust
distances computed by, e.g., MCD - covMcd().
A data frame with 75 observations on 4 variables, where the last
variable is the dependent one.
This data set is also available in package wle as
Hawkins, D.M., Bradu, D., and Kass, G.V. (1984)
Location of several outliers in multiple regression data using
Technometrics 26, 197–208.
P. J. Rousseeuw and A. M. Leroy (1987)
Robust Regression and Outlier Detection;
summary(lm.hbk <- lm(Y ~ ., data = hbk))hbk.x <- data.matrix(hbk[, 1:3])
(cHBK <- covMcd(hbk.x))
Dataset imported from https://www.r-project.org.