Computes the vector of (classical or robust)
Mahalanobis distances of all points of x
to the center of the points indexed (or weighted)
by gv
. The latter also determine
the covariance matrix.
Thought for use within fixmahal
.
1 2 3 4 5 
x 
a numerical data matrix, rows are points, columns are variables. 
n 
positive integer. Number of points. 
p 
positive integer. Number of variables. 
gv 
for 
cmax 
positive number. used in 
method 

solvecov
is used to invert the covariance matrix. The methods
"mcd"
and "mve"
in mahalanofix
do not work properly
with point constellations with singular covariance matrices!
A list of the following components:
md 
vector of Mahalanobis distances. 
mg 
mean of the points indexed by 
covg 
covariance matrix of the points indexed by 
covinv 

coll 
logical. If 
Methods "mcd"
and "mve"
require library lqs
.
Christian Hennig c.hennig@ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche/
fixmahal
, solvecov
, cov.rob
1 2 3 4 5 6  x < c(1,2,3,4,5,6,7,8,9,10)
y < c(1,2,3,8,7,6,5,8,9,10)
mahalanofix(cbind(x,y),gv=c(0,0,0,1,1,1,1,1,0,0))
mahalanofix(cbind(x,y),gv=c(0,0,0,1,1,1,1,0,0,0))
mahalanofix(cbind(x,y),gv=c(0,0,0,1,1,1,1,1,0,0),method="mcd")
mahalanofuz(cbind(x,y),gv=c(0,0,0.5,0.5,1,1,1,0.5,0.5,0))

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