Sum of squares block weighting

Description

Sum of squares block weighting: allows to scale blocks of variables, but keeping the relative weights of the variables inside a block.

Usage

blockNorm(X,targetnorm=1)

Arguments

Details

The function computes a scaling factor, which, multiplied by the input matrix, produces a matrix with a pre–determined sum of squares.

Value

a list with components Xscaled, the scaled matrix and f, the scaling factor

Note

This is a R port of the ‘MBnorm.m’ function of the MB matlab toolbox by Fran van den Berg (http://www.models.life.ku.dk/~courses/MBtoolbox/mbtmain.htm)

Author(s)

Antoine Stevens

References

Eriksson, L., Johansson, E., Kettaneh, N., Trygg, J., Wikstrom, C., and Wold, S., 2006. Multi- and Megavariate Data Analysis. MKS Umetrics AB.

See Also

blockScale, standardNormalVariate, detrend

Examples

X <- matrix(rnorm(100),ncol=10)
# Block normalize to sum of square = 1
res <- blockNorm(X,1)
sum(res$Xscaled^2) # check

Results