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 <Tranlm at 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
>
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--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/