The hemophilia data set contains two measured variables on
75 women, belonging to two groups: n1=30 of them are
non-carriers (normal group) and n2=45 are known hemophilia
A carriers (obligatory carriers).
Usage
data(hemophilia)
Format
A data frame with 75 observations on the following 3 variables.
AHFactivity
AHF activity
AHFantigen
AHF antigen
gr
group - normal or obligatory carrier
Details
Originally analized in the context of discriminant
analysis by Habemma and Hermans (1974). The objective
is to find a procedure for detecting potential hemophilia A
carriers on the basis of two measured variables: X1=log10(AHV activity) and
X2=log10(AHV-like antigen). The first group of n1=30 women consists
of known non-carriers (normal group) and the second group of n2=45
women is selected from known hemophilia A carriers (obligatory
carriers). This data set was also analyzed by Johnson and Wichern
(1998) as well as, in the context of robust Linear Discriminant Analysis
by Hawkins and McLachlan (1997) and Hubert and Van Driessen (2004).
Source
Habemma, J.D.F, Hermans, J. and van den Broek, K. (1974)
Stepwise Discriminant Analysis Program Using Density
Estimation in Proceedings in Computational statistics, COMPSTAT'1974
(Physica Verlag, Heidelberg, 1974, pp 101–110).
References
Johnson, R.A. and Wichern, D. W. Applied Multivariate
Statistical Analysis (Prentice Hall, International
Editions, 2002, fifth edition)
Hawkins, D. M. and McLachlan, G.J. (1997)
High-Breakdown Linear Discriminant Analysis
J. Amer. Statist. Assoc.92 136–143.
Hubert, M., Van Driessen, K. (2004) Fast and robust discriminant analysis,
Computational Statistics and Data Analysis, 45
301–320.
Examples
data(hemophilia)
plot(AHFantigen~AHFactivity, data=hemophilia, col=as.numeric(as.factor(gr))+1)
##
## Compute robust location and covariance matrix and
## plot the tolerance ellipses
(mcd <- CovMcd(hemophilia[,1:2]))
col <- ifelse(hemophilia$gr == "carrier", 2, 3) ## define clours for the groups
plot(mcd, which="tolEllipsePlot", class=TRUE, col=col)