heplots: Mahalanobis – R documentation

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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", ...)

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, ignoring the `method` argument.
`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, just to make this argument explicit`
`...`	other arguments passed to `cov.rob`

Details

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

Value

A numeric vector of squared Mahalanobis distances corresponding to the rows of x.

Author(s)

Michael Friendly

Examples

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

heplots

Visualizing Hypothesis Tests in Multivariate Linear Models

v1.3-8

GPL (>= 2)

Authors

John Fox [aut], Michael Friendly [aut, cre], Georges Monette [ctb], Phil Chalmers [ctb]

Initial release

2021-01-20