2 ## Description: screens meaningful variables and performns
3 ## data transformation on clustering
8 ## Description: Steinley & Brusco (2006) data transform to cluster
9 StBrtransform <- function(X){
10 apply(X, 2, function(x) 12 * var(x) / (max(x) - min(x))^2 )
14 ## Description: Clustering index (Steinley & Brusco (2006))
15 CI <- function(X, B = 1000) { # B : number of boostrap replications
20 #ci <- apply(X, 2, function(x) 12 * var(x) / (max(x) - min(x))^2 )
21 ci <- StBrtransform(X)
27 newRange <- apply(Xstar, 2, function(x) max(x) - min(x))
29 rmin <- newRange[minV]
31 datat <- array(0.0, dim = dim(X))
33 # Reweighting X into datat
36 temp <- rc[i] * (rmin / newRange[i])^2
37 datat[, i] <- sqrt(temp) * v
40 xboot <- matrix(rnorm(n * B), nrow = n)
41 #cinorm <- apply(xboot, 2, function(x) 12 * var(x) / (max(x) - min(x))^2 )
42 cinorm <- StBrtransform(xboot)
43 ci95 <- median(cinorm)
45 #ciStar <- apply(datat, 2, function(x) 12 * var(x) / (max(x) - min(x))^2 )
46 ciStar <- StBrtransform(datat)
47 selectv <- which(ciStar > ci95)
49 return(list(selectv = selectv,
56 #test <- matrix(rnorm(200), 40, 5)