Hi Linh, Here is an approach:
f <- function(v) { v <- v/sum(v) (v[1]^2) + (2 * v[2]^2) + (3*v[3]^2) } (res <- optim(c(.6, .3, .1), f)) res$par/sum(res$par) This is a downright lazy way to implement the constraint. The main idea is to combine all three functions into one function that takes a vector of parameters (v, in this case). Cheers, Josh On Thu, Jul 19, 2012 at 10:24 AM, Linh Tran <tra...@berkeley.edu> wrote: > Hi fellow R users, > > I am desperately hoping there is an easy way to do this in R. > > Say I have three functions: > > f(x) = x^2 > f(y) = 2y^2 > f(z) = 3z^2 > > constrained such that x+y+z=c (let c=1 for simplicity). > > I want to find the values of x,y,z that will minimize f(x) + f(y) + f(z). > > I know I can use the optim function when there is only one function, but > don't know how to set it up when there are three. > > I would also like to apply this to higher dimensions (i.e. for more than > three functions) if possible. > > Thank you for all your help! > > -- > Kind regards, > > Linh Tran, MPH > > ______________________________________________ > 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. -- Joshua Wiley Ph.D. Student, Health Psychology Programmer Analyst II, Statistical Consulting Group University of California, Los Angeles https://joshuawiley.com/ ______________________________________________ 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.