beta distribution formula

How is Gamma function discovered? It proves that \ begin {Align *} B (m, n) = \ int_0 ^ 1 x ^ {M-1} (32a) ^ {n-1} \ Text {d} X = \ frac {\ gamma (m) \ gamma (n)} {\ gamma (m + n )} \ end {Align *} So \ begin {Align *} f _ {m, n} (X) =\begin {cases} \

http://blog.csdn.net/shuimu12345678/article/details/307739290-1 Distribution:In one experiment, either 0 or 1 distribution, called 0-1 distribution.Two items distributed:To do the N-1-p experiment, the probability of 1 for each experiment was p, the

This article by leftnoteasy original, can be reproduced, but please keep the source and this line, if there is commercial purpose, please contact the author wheeleast@gmail.com   I. Bayesian theorem: Bayesian Theorem explains common knowledge

Theshortletdistribution Dirichlet distribution (PRML2.2.1) Dirichlet distribution can be seen as distribution above the distribution. To understand this sentence, let's take an example: Suppose we have a dice with six sides: {1, 2, 3, 4, 5, 6 }. Now

3.1 Two-Point Distribution and even distribution1. Two-Point DistributionMany random events have only two results. If the result of the product is qualified or unqualified, the product or reliable work may fail. This type of random event variable

The Bounded distribution is a method that greatly simplifies Bayesian analysis. The function of this function is to make the unknown parameters of these distributions give physical meaning before the test when the Bayesian formula contains multiple

For example, a random value rand (range: 1-100) is generated ). The probability of a small value in rand is very high, but the probability of a large value is very low. I hope you can give a specific formula. The random value can be replaced by rand.

Dirichlet distributions can be seen as distributions above the distribution. How to understand this sentence, we can 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 throw experiments,

Exponential family (exponential distribution family) is a common concept, but its definition is not particularly clear, today look at the wiki content, have a general understanding, first and share with you. This article is basically the translation

Multinomial distribution The corresponding multivariate distribution can be obtained by extending the two-yuan case of two-yuan distribution to multiple variables. First, the Bernoulli distribution is extended to the multivariate hypothesis for the