Hi R-list, I am new to optimization in R and would appreciate help on the following question. I would like to minimize the following function using two constraints:
###### fn <- function(par,H,F){ fval <- 0.5 * t(par) %*% H %*% par + F%*% par fval } # matrix H is (n by k) # matrix F is (n by 1) # par is a (n by 1) set of weights # I need two constraints: # 1. each element in par needs to be between 0 and 1 # 2. sum(par)=1 i.e. the elements in par need to sum to 1 ## I try to use optim res <- optim(c(runif(16),fn, method="L-BFGS-B", H=H, F=f ,control=list(fnscale=-1), lower=0, upper=1) ###### If I understand this correctly, using L-BFGS-B with lower=0 and upper=1 should take care of constraint 1 (box constraints). What I am lacking is the skill to include constraint no 2. I guess I could solve this by reparametrization but I am not sure how exactly. I could not find (i.e. wasn't able to infer) the answer to this in the archives despite the many comments on optim and constrained optimization (sorry if I missed it there). I am using version 2.1.1 under windows XP. Thank you very much. Jens ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html