Hello all, I am trying to do a Latin Hypercube Sampling (LHS) to a 5-parameter design matrix. I start as follows:
library(lhs) p1<-randomLHS(1000, 5) If I check the distribution of each parameter (column), they are perfectly uniformly distributed (as expected).For example, hist(p1[,1]) Now the hard (maybe strange) question. I want the combination of the first three parameters to sum up to 1 (which obviously do not) s<-p1[,1]+p1[,2]+p1[,3] s==1 It occurred to me to divide each of these parameters with the sum (vector "s" above). However the uniform distribution is lost (example for parameter 1 - first column): par1.transf<-p1[,1]/s hist(par1.transf) So, is there a way to maintain the random LHS (with uniformly distributed parameters) so that the refered condition is fulfilled? Any suggestions would be much welcome. Thanks, Duarte ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
