Linda, I assume you have 1000 triples (Power, Delay,Angle). What to do may depend on what you feel you can assume on the basis of knowledge of the subject.
At the non-parametric extreme, for each pair (Delay,Angle) and each p you have the proportion of triples with Power <=p. That is the empiric cdf of Power given (Delay,Angle). Presumably, you would like something a little more useful in the sense that it can be used to create predictions. If you have a physical basis to assume that, there are functions f, g and h such that f( Power) is a normal variable with mean a linear combination of g(Delay) and h(Angle) with variance independent of Delay and Angle, you could do a regression f(Power) = b0+b1*f(Delay)+b2*h(Angle). You might want to plot some graphs holding Delay(Angle) constant to see how Power varies and get ideas for appropriate functions. Also, check if there are engineering or physics texts on the subject already that give the distribution of Power given Delay and Angle for data similar to your sample Good Luck. Ellen Hertz "Linda" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED]... > Helloo.. > > I am having some problems in understanding this and I hope someone out > there are willing to explain it to me. > > I have 3 RVs (Power,P Delay,t and Angle,a) each with 1000 samples > estimated from real time measurements. I would like to find PDF of the > Power given their corresponding Delay & Angle i.e. f(P|t,a). How do I > do that practically? > > Thanks. > > Linda . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
