On Tue, Oct 20, 2015 at 11:58 AM, Andy Yuan <yuan...@gmail.com> wrote: > > Please could you help me to select the most appropriate/fastest function to > use for the following constraint optimisation issue? > > Objective function: > > Min: Sum( (X[i] - S[i] )^2) > > Subject to constraint : > > Sum (B[i] x X[i]) =0 > > where i=1…n and S[i] and B[i] are real numbers > > Need to solve for X > > Example: > > Assume n=3 > > S <- c(-0.5, 7.8, 2.3) > B <- c(0.42, 1.12, 0.78) > > Many thanks
I believe you can solve *analytically* your optimization problem, with the Lagrange multipliers method, Andy. By doing so, you can derive clean and closed-form expression for the optimal solution. Paul ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
