I was wondering if the following is true, where * denotes convolution:
p(A|C,D) = p(A|B) * p(B|C,D).
Basically, I want to know if convolution will marginalize out B. My intuition says this is correct, but I'm not entirely certain.
I am interested in estimating E[g(h(X))] where...
- X ~ Normal(mu,sigma)
- h(.) = CDF of Standard Normal distribution
- g(.) = inverse CDF of Beta distribution with known parameters alpha and beta
Any suggestions as to how to proceed? Taylor approximation?
Any help appreciated.
I have the probability distribution Functions(PDF) of the wind speeds of two wind sites which have a certain Pearson's correlation coefficient. How can I combine the PDFs of these two sites?
I don't have the time stamped data of these two sites, rather, I only have the distributions and...