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        两个 beta 分布的乘积

        时间:2023-10-19
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                • 本文介绍了两个 beta 分布的乘积的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                  问题描述

                  假设我有两个随机变量:

                  Say I have two random variables:

                  X ~ Beta(α1,β1)

                  X ~ Beta(α1,β1)

                  Y ~ Beta(α2,β2)

                  Y ~ Beta(α2,β2)

                  我想计算 Z = XY(随机变量的乘积)的分布

                  I would like to compute distribution of Z = XY (the product of the random variables)

                  使用 scipy,我可以获得单个 Beta 版的 pdf:

                  With scipy, I can get the pdf of a single Beta with:

                  from scipy.stats import beta
                  rv = beta(a, b)
                  x = np.linspace(start=0, stop=1, num=200)
                  my_pdf = rv.pdf(x)
                  

                  但是两个 Beta 的乘积呢?我可以分析吗?(Python/Julia/R 解决方案很好).

                  But what about the product of two Betas? Can I do this analytically? (Python/Julia/R solutions are fine).

                  推荐答案

                  对于分析解决方案,请查看 这篇论文和这个答案.

                  For an analytical solution, have a look at this paper and this answer.

                  R

                  set.seed(1) # for reproducability
                  
                  n <- 100000 # number of random variables
                  
                  # first beta distribution
                  a1 <- 0.5
                  b1 <- 0.9
                  X <- rbeta(n, a1, b1)
                  
                  # second beta distribution
                  a2 <- 0.9
                  b2 <- 0.5
                  Y <- rbeta(n, a2, b2)
                  
                  # calculate product
                  Z <- X * Y
                  
                  # Have a look at the distributions
                  plot(density(Z), col = "red", main = "Distributions")
                  lines(density(X), lty = 2)
                  lines(density(Y), lty = 2)
                  

                  这篇关于两个 beta 分布的乘积的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!

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