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# calars(), SA computation of lars()
# arguments:
# cls: 'parallel' cluster
# larscmd: a call to lars(), quoted
# outfl: name of output file
# calars <- function(cls,ddf,xcols,ycol,type='lasso',outfl=NULL) {
calars <- function(cls,larscmd,outfl=NULL) {
cmd <- paste('larsout <- ',larscmd,sep='')
# larsouts <- doremotecmd(cls,cmd)
larsouts <- doclscmd(cls,cmd)
if (!is.null(outfl))
save(larscmd,file=outfl)
}
# executes the command in the string cmd at the worker nodes of the
# cluster
doremotecmd <- function(cls,cmd) {
clusterExport(cls,'cmd',envir=environment())
clusterEvalQ(cls,docmd(cmd))
}
# library(partools)
# cls <- makeCluster(2)
# setclsinfo(cls)
# data(prgeng)
# pe <- prgeng
# distribsplit(cls,'pe')
# clusterEvalQ(library(lars))
# calars(cls,'lars(as.matrix(pe[,c(7,8)]),pe[,8])')
# clusterEvalQ(cls,head(x))
#
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