Re: [R] optimization problem in R ... can this be done?

From: Spencer Graves <>
Date: Sun 26 Jun 2005 - 04:16:11 EST

          Part of the R culture is a statement by Simon Blomberg immortalized in library(fortunes) as, "This is R. There is no if. Only how."

          I can't see now how I would automate a complete solution to your problem in general. However, given a specific g(x, n), I would start by writing a function to use "expand.grid" and "contour" to make a contour plot of g(x, n) over specified ranges for x = seq(0, x.max, length=npts) and n = seq(0, n.max, npts) for a specified number of points npts. Then I'd play with x.max, n.max, and npts until I got what I wanted. With the right choices for x.max, n.max, and npts, the solution will be obvious from the plot. In some cases, nothing more will be required.

          If I wanted more than that, I would need to exploit further some specifics of the problem. For that, permit me to restate some of what I think I understood of your specific problem:

          (1) For fixed n, g(x, n) is monotonically decreasing in x>0.

          (2) For fixed x, g(x, n) has only two local maxima, one at n=0 (or n=eps>0, esp arbitrarily small) and the other at n2(x), say, with a local minimum in between at n1(x), say.

          With this, I would write functions to find n1(x) and n2(x) given x. I might not even need n1(x) if I could figure out how to obtain n2(x) without it. Then I'd make a plot with two lines (using "plot" and "lines") of g(x, 0) and g(x, n2(x)) vs. x.

          By the time I'd done all that, if I still needed more, I'd probably have ideas about what else to do.

	  hope this helps.  		
	  spencer graves

Gregory Gentlemen wrote:

> Im trying to ascertain whether or not the facilities of R are sufficient for solving an optimization problem I've come accross. Because of my limited experience with R, I would greatly appreciate some feedback from more frequent users.
> The problem can be delineated as such:
> A utility function, we shall call g is a function of x, n ... g(x,n). g has the properties: n > 0, x lies on the real line. g may take values along the real line. g is such that g(x,n)=g(-x,n). g is a decreasing function of x for any n; for fixed x, g(x,n) is smooth and intially decreases upon reaching an inflection point, thereafter increasing until it reaches a maxima and then declinces (neither concave nor convex).
> My optimization problem is to find the largest positive x such that g(x,n) is less than zero for all n. In fact, because of the symmetry of g around x, we need only consider x > 0. Such an x does exists in this problem, and of course g obtains a maximum value of 0 at some n for this value of x. my issue is writing some code to systematically obtain this value.
> Is R capable of handling such a problem? (i.e. through some sort of optimization fucntion, or some sort of grid search with the relevant constraints)
> Any suggestions would be appreciated.
> Gregory Gentlemen
> The following is a sketch of an optimization problem I need to solve.
> __________________________________________________
> [[alternative HTML version deleted]]
> ______________________________________________
> mailing list
> PLEASE do read the posting guide!

Spencer Graves, PhD
Senior Development Engineer
PDF Solutions, Inc.
333 West San Carlos Street Suite 700
San Jose, CA 95110, USA <>
Tel:  408-938-4420
Fax: 408-280-7915

______________________________________________ mailing list
PLEASE do read the posting guide!
Received on Sun Jun 26 05:41:31 2005

This archive was generated by hypermail 2.1.8 : Fri 03 Mar 2006 - 03:33:02 EST