prospectr (version 0.1.3)

e2m: A function for transforming a matrix from its Euclidean space to its Mahalanobis space

Description

A function for transforming a matrix from its Euclidean space to its Mahalanobis space

Usage

e2m(X, sm.method = c("svd", "eigen"))

Examples

# test data
## Not run: 
# X <- matrix(rnorm(500),ncol=5)
# # Normal way to compute the Mahalanobis distance
# md1 <- sqrt(mahalanobis(X, center = colMeans(X), cov = cov(X)))
# # Projection approach for computing the Mahalanobis distance
# #1. Projecting from the Euclidean to the Mahalanobis space
# Xm <- e2m(X, sm.method = 'svd')
# #2. Use the normal Euclidean distance on the Mahalanobis space
# md2 <- sqrt(rowSums((sweep(Xm, 2, colMeans(Xm), '-'))^2))
# # Plot the results of both methods
# plot(md1, md2)
# # Test on a real dataset
# #Mahalanobis in the spectral space
# data(NIRsoil)
# X <- NIRsoil$spc
# Xm <- e2m(X, sm.method = 'svd')
# md2 <- sqrt(rowSums((sweep(Xm, 2, colMeans(Xm), '-'))^2))
# 
# md1 <- sqrt(mahalanobis(X, center = colMeans(X), cov = cov(X))) # does not work#'
# #Mahalanobis in the PC space
# pc <- 20
# pca <- prcomp(X, center=TRUE,scale=TRUE)
# X <- pca$x[, 1:pc]
# X2 <- sweep(pca$x[,1:pc,drop=FALSE],2,pca$sdev[1:pc],'/')
# md4 <- sqrt(rowSums((sweep(Xm, 2, colMeans(Xm), '-'))^2))
# md5 <- sqrt(rowSums((sweep(X2, 2, colMeans(X2), '-'))^2))
# md3 <- sqrt(mahalanobis(X, center = colMeans(X), cov = cov(X))) # does work
# ## End(Not run)