# Re: bayesian update hyperparameters

*From*: "Anon." <bob.ohara@xxxxxxxxxxx>*Date*: Fri, 13 Jul 2007 21:13:22 +0300

erehwon wrote:

Hello,Prior for which parameters? Obviously not the probabilities (unless m=2), as they are constrained to add up to 1.

If I'm determining a posterior (multinomial) distribution based on

observed data, and if the chosen prior distribution is just the uniform

distribution, then there aren't any hyperparameters right?

(I have seen that when the prior distribution is Dirichlet, then there is aNo, the Dirichlet has as many parameters as there are classes.

single hyperparameter, but I believe this is different scenario...but I'm

not entirely sure.)

The Dirichlet is the conjugate prior for the multinomial, and setting alpha=1 for all classes is equivalent to using a uniform distribution.

Bob

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Bob O'Hara

Department of Mathematics and Statistics

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**Follow-Ups**:**Re: bayesian update hyperparameters***From:*Joel

**References**:**bayesian update hyperparameters***From:*erehwon

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