heplots (version 1.6.2)

Mahalanobis: Classical and Robust Mahalanobis Distances

Description

This function is a convenience wrapper to mahalanobis offering also the possibility to calculate robust Mahalanobis squared distances using MCD and MVE estimators of center and covariance (from cov.rob)

Usage

Mahalanobis(
  x,
  center,
  cov,
  method = c("classical", "mcd", "mve"),
  nsamp = "best",
  ...
)

Value

a vector of length nrow(x) containing the squared distances.

Arguments

x

a numeric matrix or data frame with, say, \(p\) columns

center

mean vector of the data; if this and cov are both supplied, the function simply calls mahalanobis to calculate the result

cov

covariance matrix (p x p) of the data

method

estimation method used for center and covariance, one of: "classical" (product-moment), "mcd" (minimum covariance determinant), or "mve" (minimum volume ellipsoid).

nsamp

passed to cov.rob

...

other arguments passed to cov.rob

Author

Michael Friendly

Details

Any missing data in a row of x causes NA to be returned for that row.

See Also

mahalanobis, cov.rob

Examples

summary(Mahalanobis(iris[, 1:4]))
summary(Mahalanobis(iris[, 1:4], method="mve"))
summary(Mahalanobis(iris[, 1:4], method="mcd"))