This looks much like the kinds of problems that function 'solve.QP' in
package 'quadprog' can handle. But if you want people to help you,
follow the posting guide and 'provide commented, minimal,
self-contained, reproducible code'. You need to show people what you
tried and how it failed (so
try the lsei function from the limSolve package.
On Mon, Dec 19, 2011 at 2:32 PM, Russell2 wrote:
> Dear All
>
> I have a constrained optimisation problem, I want to maximise the following
> function
>
> t(weights) %*% CovarianceMatrix %*% weights
>
> for the weights,
>
> subject to constraints
02, 2009 3:32 PM
To: 'Iason Christodoulou'
Cc: r-help@r-project.org
Subject: Re: [R] constrained optimisation in R.
Hi,
I know nothing about neither your model nor the Skellam distribution. I
will assume that it is a sensible model and that the parameters are
identifiable from the data.
h/People/Faculty_personal_pages/Varadhan.h
tml
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From: Iason Christodoulou [mailto:c_iaso...@hotmail.com]
Sent: Thursday, July 02, 2009 2:58 PM
To: rvarad...@jhmi.edu
Subject: RE: [R] constrained optimisation in R.
$B&3(Bhe actual problem is:
Log ($B&K(
Please tell us about the actual problem that you are trying to solve,
because the "answer" would very much depend on that.
Are your constraints really sum(par) = 0? If so, you can just eliminate one
of the parameters and solve the optimization problems with (p-1) parameters.
If you have other c
On Wed, Mar 12, 2008 at 11:29 AM, giovanna menardi
<[EMAIL PROTECTED]> wrote:
> i have to optimise a function f(a,b), with a, b vectors in R^d such that a
> and b are orthogonal, that is a'b=0. Anybody has a suggestion?
And your function f(a,b) is defined by?
Paul
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