First you have to be more specific, what are actually the parameters of the
function that
you want to optiomize and what are actually constants.
So you would need to specify your objective function
"function(theta)=lambda*(Constr)^2-f(x,theta)" (which is not realy writen
the R-way)
as
fun<-function(Constr,theta){lambda*(Constr)^2-f(x,theta)}
However, since, if I understand correclty, you don't want Constr to be
smaller or equal to d, you should somehow build this into your objective
function, like:
fun<-function(Constr,theta){lambda*(Constr)^2-f(x,theta)+ifelse(Constr<=d,
Inf, 0)}
I hope this helps,
Ales Ziberna
- Original Message -
From: "Vicky Landsman" <[EMAIL PROTECTED]>
To:
Sent: Thursday, March 24, 2005 8:38 PM
Subject: [R] How to stop the minimization when the condition does not hold
Dear experts!
I have a minimization problem with non-linear constraint and Objective
function(theta)=lambda*(Constr)^2-f(x,theta). Theta is a vector of
parameters.
I'd like to stop the optimization after the value of the constraint is
less
or equal some constant value, say d, and save the last computed value of
the
function.
For this purpose, I thought to define the Objective function like this:
if (Constraint>d) fun<-
else stop
but this does not work with error message:
Error in f(x, ...) : Object "fun" not found
I am using nlm for minimization.
Thanks a lot for help and suggestions,
Vicky Landsman.
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