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catman
2006 Mar 23
0
Writing a function to fit ALSOS models. problem with normalization?
...= nx = x
mx[] = 0
nx[] = 0
for (i in (1:ncol(x))[x.facs]) {
# optimal scaling
if (i==1) nx[,i] = ols$fitted.values
else nx[,i] = (x[,1] - cbind(rep(1,nrow(x)), x[,c(-1,-i)]) %*% b[-i])/b[i]
# create within-category means
tmpfac = factor(ox[,i], labels=1:nlevels(ox[,i]))
catmeans = tapply(nx[,i], tmpfac, mean)
# ensure ordinal values are correctly ordered
if (x.ords[i]) {
tmp = kruskal.ordering(nx[,i], tmpfac)
tmpfac = tmp$tmpfac
catmeans = tmp$catmeans
}
# set values to within-category means
mx[,i] = catmeans[tmpfac]
# normalize according...