Sufficient statistics for beta-binomial distribution

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The beta-binomial pmf is

$$f_X(x) = {n \choose x}{B(x+\alpha, n-x+\beta)\over B(\alpha, \beta)}$$

where $B$ is the beta function.

The numerator is the issue here when trying to separate data from parameters. I tried using

$$B(x+\alpha, n-x+\beta) \propto \Gamma(y+\alpha)\Gamma(n-x+\beta)$$

and the fact that $x$ is discrete but that led me to a polynomial where parameters and data are still intertwined through the exponents and coefficients.

Is this solvable at all?

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Here, we have $p(y|\theta)$ is our data from a Binomial distribution, parameters $n,p$. And $p(\theta)$ is from a Beta distribution, parameters $a=1,b=1$ for simplicity. The final image shows that the hyper parameters are just additive, where $dbeta$ is essentially the Binom-Beta distribution.

Sourced from "A First Course in Bayesian Statistical Methods"

Sourced from "A First Course in Bayesian Statistical Methods"

Sourced from "A First Course in Bayesian Statistical Methods"

Sourced from "A First Course in Bayesian Statistical Methods"