maha {GenAlgo} | R Documentation |
Compute the (squared) Mahalanobis distance between two groups of vectors
Description
The Mahalanobis distance between two groups of vectors
Usage
maha(data, groups, method = "mve")
Arguments
data |
A matrix with columns representing features (or variables) and rows representing independent samples |
groups |
A factor or logical vector with length equal to the number of rows
(samples) in the |
method |
A character string determining the method that should be used to
estimate the covariance matrix. The default value of " |
Details
The Mahalanobis distance between two groups of vectors is the distance between their centers, computed in the equivalent of a principal component space that accounts for different variances.
Value
Returns a numeric vector of length 1.
Author(s)
Kevin R. Coombes krc@silicovore.com, P. Roebuck proebuck@mdanderson.org
References
Mardia, K. V. and Kent, J. T. and Bibby, J. M.
Multivariate Analysis.
Academic Press, Reading, MA 1979, pp. 213–254.
See Also
Examples
nFeatures <- 40
nSamples <- 2*10
dataset <- matrix(rnorm(nSamples*nFeatures), ncol=nSamples)
groups <- factor(rep(c("A", "B"), each=10))
maha(dataset, groups)