mahalanobis(x, center, cov, inverted=F)
NAs) are allowed.
center must equal the number of columns in
x.
Missing values are not accepted.
x.
This may alternatively be a QR decomposition of the covariance matrix,
or the inverse of the covariance matrix (see
inverted).
Missing values are not accepted.
TRUE, then
cov is taken to be the inverse of the
covariance matrix.
x.
The result contains missing values for rows of
x that contain missing values.
The
ith element of the result is equal to
(x[i,]-center)%*%solve(cov)%*%(x[i,]-center)
.
The Mahalanobis distance is discussed in many multivariate books such as:
Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979).
Multivariate Analysis.
Academic Press, London.
freeny.cov <- cov.mve(freeny.x) freeny.mah <- mahalanobis(freeny.x, freeny.cov$center, freeny.cov$cov)