At 02:40 AM 4/29/2008, Arun Kumar Saha wrote:

>Here I am in a simulation study where I want to find different values

>of x and y such that f(x,y)=c (some known constant) w.r.t. x, y >0,

>y<=x and x<=c1 (another known constant). Can anyone please tell me how

>to do it efficiently in R. One way I thought that I will draw

>different random numbers from uniform dist according to that

>constraints and pick those which satisfy f(x,y)=c. However it is not I

>think computationally efficient. Can anyone here suggest me any other

>efficient approach?

You have not specified the distributions proper for X and Y. Using a

uniform distribution is only appropriate when it meets requirements.

One obvious approach is to sample one of the variables, say X, and

then solve your equation for Y. If you're going to draw a lot of

samples, it would pay to develop y = g(x) first.

But you need to know how to sample X in the first place. Is its

distribution uniform, or something else?

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Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail:

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