Hi!
I have a series of observations of 2 random variables (say X and Y) from my
measurement data. These 2 RVs are not independent and hence f(X,Y) ~=
f(X)f(Y). Hence, I can't investigate f(X) and f(Y) separately. I tried to
plot the 2-D kernel density estimates of these 2 RVs and from the it looks
like Laplacian/Gaussian/Generalised Gaussian shape in one side and the other
side looks like Gamma/Weibull/Exponential shape.
My intention is to find the joint 2-D distribution of these 2 RVs so that I
can reprenseted this by an equation (so that I could regenerate this plot
using simulation later on). I wonder whether anyone has come across this
kind of problem and what method that I should use??
Thanks...
Regards,
CCC
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