如何生成具有不同边际分布的多元随机数? [英] How to generate multivariate random numbers with different marginal distributions?

问题描述

我对如何生成一些双变量随机树丛一无所知，例如在copula中.边缘具有不同的分布，即t，γ，并且关节结构可以是高斯或t.我将不得不修理他们的肯德尔牛头犬.而且我想研究一下这些随机数的皮尔逊Rho与预设的tau有何不同.

I have lost idea how to generate some bivariate random mumbers, say in copula. The marginals are of different distribution, i.e. t, gamma, and the joint structure can be gaussian or t. I will have to fixed their kendall tau. And I want to examine how the pearson rho of those random numbers are different from the presetted tau.

有什么建议吗?高度赞赏R/Matlab中的一个原型！

Any suggestion? A piece of prototype in R/Matlab is highly appreciated!

推荐答案

如果具有统计工具箱，则可以使用函数copularnd从系动词生成随机数.文档中有几个示例.要在使用Kendall的tau和Pearson的rho之间进行转换，请查看copulaparam和copulastat.

If you have Statistics Toolbox you can generate random numbers from copulas using the function copularnd. There are several examples in the documentation. To convert between using Kendall's tau and Pearson's rho, take a look at copulaparam and copulastat.

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