mahalDist: Get squared Mahalanobis distances for N observations in M...

In davebraze/FDB1: A brew of utility and convenience functions

Usage

mahalDist(m, scale = TRUE, use = "complete.obs", center = "mean")

Arguments

m	A data.frame or matrix. Observations in rows.
scale	If TRUE, scale variables before getting mahalanobis distances.
use	Observations to use in computing covariance matrix. Gets passed to cov.
center	Type of univariate center for each variable in m; "mean" or "median"

Details

Get squared Mahalanobis distances for N observations in M dimensions. This is a convenience wrapper around mahalanobis, which see. Variables are optionally scaled before distances are computed. Incomplete observations will return NA.

Value

A list with additional class "mahalDist" containing elements:

1. D2: A vector of squared Mahalanobis distances for observations (rows) in m. Incomplete observations return NA.

2. vars: A character vector with the column names from m.

3. dim: The number of columns of m.

Author(s)

Dave Braze [e-mail]

See Also

mahalanobis

cov

davebraze/FDB1 documentation built on May 14, 2019, 8:59 p.m.