Joint pmf of 2 binomially distributed random variables

AI Thread Summary
The discussion centers on finding the joint probability mass function (pmf) of two binomially distributed random variables, A and R, where A follows a BIN(n1, p1) distribution and R follows a BIN(n2, p2) distribution. The user expresses concern about the challenges posed by the fact that P(R=0) is greater than zero, leading to the possibility of X being infinite. They acknowledge that using the Jacobian method for discrete distributions is not standard practice but feel compelled to do so in this case. The conversation highlights the complexities involved in deriving the joint pmf under these conditions. The difficulties in handling the infinite probability of X are a central focus of the discussion.
cimmerian
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I hope I wrote that correctly but I'm trying to find the joint. I heard it was impossible from someone.

X = A/R
A~BIN(n1, p1)
R~BIN(n2, p2)

I know I shouldn't be using the Jacobian method for Discrete distributions but I have to do it anyway.

Anyone know?
 
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The major difficulty arises from the fact that P(R=0) > 0, so you have a non-zero probability of X being infinite.
 

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