Distribution of exponential family

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Discussion Overview

The discussion revolves around the characterization of a probability function for a two-variable random variable in the context of the exponential family of distributions. Participants explore how to express the given probability function in canonical form, which is essential for deriving statistical properties such as expected values and variance matrices.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant presents a probability function involving two variables and expresses confusion about writing it in canonical form, noting their familiarity is limited to single-variable exponential families.
  • Another participant outlines the necessary factorized form for a two-vector random variable to belong to the exponential family, specifying the roles of various functions involved.
  • A repeated inquiry from the first participant seeks clarification on whether they can derive functions h(z) and g(γ) from their probability function.
  • A later post requests assistance in transforming their revised model into canonical form to facilitate the calculation of expected values and variance matrices.
  • Another participant expresses a desire for help specifically with finding the variance and expected value, indicating a focus on practical outcomes rather than theoretical formulation.

Areas of Agreement / Disagreement

The discussion does not appear to reach consensus, as participants express varying levels of understanding and seek different forms of assistance regarding the exponential family representation and statistical calculations.

Contextual Notes

Participants have not fully resolved the assumptions necessary for expressing the probability function in canonical form, and there are unresolved mathematical steps related to the transformation of the model.

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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