"Turn" Dirichlet distribution

(Note: Only a little bit of information is forwarded for future reference.) Interested students please visit the original details. ）

Dirichlet distributions can be seen as distributions above the distribution. How to understand this sentence, we can first give an example: suppose we have a dice, it has six sides, respectively, {1,2,3,4,5,6}. Now we have done 10,000 throws experiment, obtained the experiment result is six sides respectively appeared {2000,2000,2000,2000,1000,1000} times, if uses each side to appear the frequency and the test total ratio to estimate this surface occurrence probability, then we obtained six surface occurrence probability, {0.2,0.2,0.2,0.2,0.1,0.1}, respectively. Now, we're not satisfied, we want to do 10,000 trials, we throw dice 10,000 times in each experiment. We want to know that the occurrence of this situation makes us think that the probability of {0.2,0.2,0.2,0.2,0.1,0.1} on the six side of the dice is (perhaps the probability of the next test statistic is {0.1, 0.1, 0.2, 0.2, 0.2, 0.2}). So we're thinking about the distribution above the distribution of the probability distribution on the six side of the dice. And such a distribution is Dirichlet distribution.

=====================

Another: Wikipedia Dirichlet distribution

"Turn" Dirichlet distribution