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| hbk   | R Documentation   |
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Hawkins, Bradu, Kass's Artificial Data
--------------------------------------

Description
~~~~~~~~~~~

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().

Usage
~~~~~

::

    data(hbk)

Format
~~~~~~

A data frame with 75 observations on 4 variables, where the last
variable is the dependent one.

X1
    x[,1]

X2
    x[,2]

X3
    x[,3]

Y
    y

Note
~~~~

This data set is also available in package wle as ``artificial``.

Source
~~~~~~

Hawkins, D.M., Bradu, D., and Kass, G.V. (1984) Location of several
outliers in multiple regression data using elemental sets.
*Technometrics* **26**, 197–208.

P. J. Rousseeuw and A. M. Leroy (1987) *Robust Regression and Outlier
Detection*; Wiley, p.94.

Examples
~~~~~~~~

::

    data(hbk)
    plot(hbk)
    summary(lm.hbk <- lm(Y ~ ., data = hbk))

    hbk.x <- data.matrix(hbk[, 1:3])
    (cHBK <- covMcd(hbk.x))

