# Derived distribution _2

Posted 8 years ago
3311 Views
|
|
0 Total Likes
|
 Hi everyone! I'm trying do obtain the derived distribution of Q [P,EP] I know the distribution of both P and EP Here attached the code that I'm using. It runs forever...:-( Thanks! Attachments:
 I don't have answer for the general density of this probability density (and it might not even have a compact form) but for the specific parameters you use one can obtain a nonparametric density estimate as good as you like by using a large enough sample size: \[Omega] = 2.7; \[Mu]P = 700; \[Sigma]P = 200; \[Mu]EP = 800; \[Sigma]EP = 200; x1 = RandomVariate[NormalDistribution[\[Mu]P, \[Sigma]P], 1000]; x2 = RandomVariate[NormalDistribution[\[Mu]EP, \[Sigma]EP], 1000]; q = x1 (1 - (1 + (x2/x1) - (1 + (x2/x1)^\[Omega])^(1/\[Omega]))); Plot[PDF[SmoothKernelDistribution[q], x], {x, 0, 1000}] But with some samples and almost certainly with large samples, you will have issues when either x1 or x2 is negative unless Abs[x2/x1] is used (although that is likely not the variable of interest).