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# Normalisation according to Tibshirani et al #
# Author : PBG 2002; corrected 20JAN05
normalise <- function (x, linear = TRUE) {
# x <- dats
x <- as.matrix(x)
# y <- apply(x, 1, mean)
y <- t(c(rep(1/ncol(x), ncol(x)))%*%t(x))
x <- sign(x) * (abs(x))^(1/3)
y <- sign(y) * (abs(y))^(1/3)
for (i in 1:ncol(x)) {
x[, i] <- predict(lm(y ~ x[, i]), as.data.frame(x[, i]))
}
if (linear)
return(x^3)
else return(x)
}
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