Please read the help page carefully, the very first line that describes the
function says, "Minimise a function subject to linear inequality constraints".
OP has a problem with equality constraints: sum(x) = 1.
Furthermore, if you want to solve a QP problem then it is better to use a
dedicated QP algorithm than to use a general-purpose nonlinear optimization
algorithm.
Ravi.
____________________________________________________________________
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
----- Original Message -----
From: "Peng, C" <cpeng....@gmail.com>
Date: Tuesday, September 28, 2010 7:58 pm
Subject: Re: [R] constrained optimization -which package?
To: r-help@r-project.org
> constrOptim() can do linear and quadratic programming problems! See
> the
> following example from the help document.
>
> ## Solves linear and quadratic programming problems
> ## but needs a feasible starting value
> #
> # from example(solve.QP) in 'quadprog'
> # no derivative
> fQP <- function(b) {-sum(c(0,5,0)*b)+0.5*sum(b*b)}
> Amat <- matrix(c(-4,-3,0,2,1,0,0,-2,1),3,3)
> bvec <- c(-8,2,0)
> constrOptim(c(2,-1,-1), fQP, NULL, ui=t(Amat),ci=bvec)
> # derivative
> gQP <- function(b) {-c(0,5,0)+b}
> constrOptim(c(2,-1,-1), fQP, gQP, ui=t(Amat), ci=bvec)
>
> ## Now with maximisation instead of minimisation
> hQP <- function(b) {sum(c(0,5,0)*b)-0.5*sum(b*b)}
> constrOptim(c(2,-1,-1), hQP, NULL, ui=t(Amat), ci=bvec,
> control=list(fnscale=-1))
>
> --
> View this message in context:
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@r-project.org mailing list
>
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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