I am trying to use the Hmisc function transace to transform predictors
test<-cbind(flowstress,pressres,alloy)
xtrans<-transace(x,binary=pressres',monotonic='flowstress', categorical='alloy')
and I am getting the following message??
Error in ace(x[, -i], x[, i], monotone = im, categorical = ic) :
unused argument(s) (monotone ...)
Any idea?
I am trying to use the Hmisc function transace to transform predictors
test<-cbind(flowstress,pressres,alloy)
xtrans<-transace(x,binary=pressres',monotonic='flowstress', categorical='alloy')
and I am getting the following message??
Error in ace(x[, -i], x[, i], monotone = im, categorical = ic) :
unused argument(s) (monotone ...)
Any idea?
thanks anne
thank for your help
Anne
The corrected version (below) will fix that problem but note that there
is a bug in ace causing it not to allow a monotonicity constraint when a
variable is on the left hand side. This is inconsistent with the ace
documentation. There are other problems in ace in which it checks
column numbers against the number of rows in the x matrix instead of the
number of columns. The internal version of ace defined inside areg.boot
fixes the latter problem. Note that I reported these problems a long
time ago.
Frank
transace <- function(x, monotonic=NULL, categorical=NULL, binary=NULL,
pl=TRUE) {
if(.R.) require('acepack') # provides ace, avas
nam <- dimnames(x)[[2]]
omit <- is.na(x %*% rep(1,ncol(x)))
omitted <- (1:nrow(x))[omit]
if(length(omitted)) x <- x[!omit,]
p <- ncol(x)
xt <- x # binary variables retain original coding
if(!length(nam)) stop("x must have column names")
rsq <- rep(NA, p)
names(rsq) <- nam
for(i in (1:p)[!(nam %in% binary)]) {
lab <- nam[-i]
w <- 1:(p-1)
im <- w[lab %in% monotonic]
ic <- w[lab %in% categorical]
if(nam[i] %in% monotonic) im <- c(0, im)
if(nam[i] %in% categorical) ic <- c(0, ic)
m <- 10*(length(im)>0)+(length(ic)>0)
if(m==11) a <- ace(x[,-i], x[,i], mon=im, cat=ic)
else if (m==10) a <- ace(x[,-i], x[,i], mon=im)
else if(m==1) a <- ace(x[,-i], x[,i], cat=ic)
else a <- ace(x[,-i], x[,i])
xt[,i] <- a$ty
rsq[i] <- a$rsq
if(pl)plot(x[,i], xt[,i], xlab=nam[i], ylab=paste("Transformed",nam[i]))
}
cat("R-squared achieved in predicting each variable:\n\n")
print(rsq)
attr(xt, "rsq") <- rsq
attr(xt, "omitted") <- omitted
invisible(xt)
}