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Sum of squares block weighting: allows to scale blocks of variables, but keeping the relative weights of the variables inside a block.
blockNorm(X, targetnorm = 1)
data.frame or matrix to transform
data.frame
matrix
desired sum of squares for a block of variables (default = 1)
a list with components Xscaled, the scaled matrix and f, the scaling factor
list
Xscaled
f
The function computes a scaling factor, which, multiplied by the input matrix, produces a matrix with a pre--determined sum of squares.
Eriksson, L., Johansson, E., Kettaneh, N., Trygg, J., Wikstrom, C., and Wold, S., 2006. Multi- and Megavariate Data Analysis. MKS Umetrics AB.
blockScale, standardNormalVariate, detrend
blockScale
standardNormalVariate
detrend
# NOT RUN { X <- matrix(rnorm(100), ncol = 10) # Block normalize to sum of square equals to 1 res <- blockNorm(X, targetnorm = 1) sum(res$Xscaled^2) # check # }
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