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I am trying to learn about the Beta Binomial for Bayesian style probability. So far I have:

$p(D|\theta)$ is the likelihood of the data set.

$D$ is the data set.

$p(\theta)$ is the prior probability of the parameter $h$ (I would use $\theta$ instead of $h$, but for this example I'd rather use discrete probability instead of continuous).

So the posterior distribution is proportional to the likelihood times the prior:

$p(\theta|D) \propto p(D|\theta) \times p(\theta)$

My question is this: suppose we first get a data set $D_1$, and we use it to obtain a posterior distribution. But then (like batch style learning), we obtain another data set $D_2$. We first calculate the distribution given $D_1$ using the above equation, but then how do we update $\theta$ before using the equation again to obtain the new posterior from $D_2$?

Thanks in advance

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Okay, so initial the posterior is $$p(\theta|D_1)=\frac{p(D_1|\theta)p(\theta)}{\int_{\theta\in\Theta}p(D_1|\theta)p(\theta)\mathrm{d}\theta},\forall\theta\in\Theta$$ where $\Theta$ is the parameter space.

The old posterior becomes the new prior distribution. The updated posterior becomes $$p(\theta|D_1;D_2)=\frac{p(D_2|\theta)p(\theta|D_1)}{\int_{\theta\in\Theta}p(D_2|\theta)p(\theta|D_1)\mathrm{d}\theta},\forall\theta\in\Theta$$

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  • $\begingroup$ Hello Dave, when you say p(theta | D1 ; D2), you mean p( (theta|D1) | D2), correct? $\endgroup$ – Josh Jul 20 '17 at 13:31
  • $\begingroup$ One more thing, suppose you wanted to actually modify theta so that the following would be true: p(new_theta) = p(old_theta | D1) ... how would you change theta? $\endgroup$ – Josh Jul 20 '17 at 13:44
  • $\begingroup$ As to first comment, no I meant what I wrote. The probability of theta given both d1 and d2. $\endgroup$ – Dave Harris Jul 20 '17 at 16:30
  • $\begingroup$ As to second comment. It is notationally acceptable to drop the "given d1" from the posterior to make it a prior if you wish. I kept the notation in my answer so you could see the posterior was now a prior. $\endgroup$ – Dave Harris Jul 20 '17 at 16:32

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