Distribution of exponential family

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SUMMARY

The probability function p(y1,y2) = Γ(y1+y2+γ)/((y1+y2)!*Γ(γ)) represents a two-variable distribution that can be classified within the exponential family framework. To express this function in canonical form, it must be rewritten as p(y1,y2) = h(y1,y2)g(γ)exp(∑_{k=1}^s η_k(γ)T_k(y1,y2), where h, g, η_k, and T_k are known functions. The discussion emphasizes the need to identify these functions to derive the expected value and variance matrices for the random variable Z = Y1 + Y2.

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the_dane
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Let's say my probability function is given by: p(y1,y2)=Γ(y1+y2+γ)/((y1+y2)!*Γ(γ)), when γ>0 is known. I suppose it is from an exponential family but I can't write in canonical form because I'm only familiar with exponential family with one variable so I'm confused now when there's to variable. Can someone help me out here.
 
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For the distribution of a 2-vector random variable like that to be in the exponential family it must be able to be written in the factorised form

$$p(y_1,y_2)=h(y_1,y_2)g(\gamma)\exp\left(\sum_{k=1}^s\eta_k(\gamma)T_k(y_1,y_2)\right)$$

where ##s## is a non-negative integer and ##h,g, \eta_1,...,\eta_s, T_1,...,T_s## are all known functions.
 
the_dane said:
Let's say my probability function is given by: p(y1,y2)=Γ(y1+y2+γ)/((y1+y2)!*Γ(γ)), when γ>0 is known. I suppose it is from an exponential family but I can't write in canonical form because I'm only familiar with exponential family with one variable so I'm confused now when there's to variable. Can someone help me out here.
Consider the random variable ##Z=Y_1+Y_2##.

Therefore, you have:

##
\begin{eqnarray*}
\frac{\Gamma(y_1+y_2+\gamma)}{(y_1+y_2)! \ \Gamma(\gamma)} = \frac{\Gamma(z+\gamma)}{z! \ \Gamma(\gamma)} = \frac{1}{z!} \cdot \frac{1}{\Gamma(\gamma)} \cdot \Gamma(z+\gamma) \\
\end{eqnarray*}##

Do you have a function ##h(z)## and a function ##g(\gamma)## now?

Also, remember that ##a=\exp(\log(a))##! :wink:
 
Thanks for the answers. I have edited my model a lot and I'm now looking at this model. probability function for Y=(Y1,Y2) is given by p. Can anyone bring this to canonical form so I can find expected value and variance matrixes.
https://dl.dropboxusercontent.com/u/17974596/Sk%C3%A6rmbillede%202016-02-02%20kl.%2007.35.26.png
 
Last edited by a moderator:
... or just help me find the variance and expected value :)
 

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