R: Whitening transformation

whitening {fastmatrix} | R Documentation

## Whitening transformation

### Description

Applies the whitening transformation to a data matrix based on the Cholesky decomposition of the empirical covariance matrix.

### Usage

    whitening(x, Scatter = NULL)

### Arguments

`x` | vector or matrix of data with, say, p columns.
`Scatter` | covariance (or scatter) matrix (p x p) of the distribution, must be positive definite. If `NULL`, the covariance matrix is estimated from the data.

### Value

Returns the whitened data matrix \bold{Z} = \bold{X W}^T, where

\bold{W}^T\bold{W} = \bold{S}^{-1},

with \bold{S} the empirical covariance matrix.

### References

Kessy, A., Lewin, A., Strimmer, K. (2018). Optimal whitening and decorrelation. The American Statistician 72, 309-314.

### Examples

    x <- iris[,1:4]
    species <- iris[,5]
    pairs(x, col = species) # plot of Iris

    # whitened data
    z <- whitening(x)
    pairs(z, col = species) # plot of

[Package fastmatrix version 0.3-819 Index]