How do I generate samples from multivariate kernel density estimated distribution?

Question

Linus Schumacher 2018-8-6

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/413763-how-do-i-generate-samples-from-multivariate-kernel-density-estimated-distribution

评论： Linus Schumacher 2020-8-13

Unlike the univariate counterpart, there is no documentation for how to draw random samples from a multivariate kernel density estimation, as obtained from mvksdensity.

One possibility would be to query the mvksdensity at uniform random points, and accept the samples with the right probability.

Presumably one could replicate the estimated density using gmdistribution, with the number of components equal to the number of samples used in the kernel density estimation. But what is the right variance to use, and how does this relate to the bandwidth parameter used in mvksdensity?

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Linus Schumacher 2018-8-6

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/413763-how-do-i-generate-samples-from-multivariate-kernel-density-estimated-distribution#answer_331774

Ok, I've found the answer. The right sigma to use for gmdistribution seems to be bandwidth.^2

3 个评论
显示 1更早的评论隐藏 1更早的评论

Sterling Baird 2020-8-12

Do you have a reference for using bw.^2 ?

Linus Schumacher 2020-8-13

I can't remember, I either looked this up in the Matlab documentation, or tried it out with different bandwidth to make sure gmdistribution gives me the same results as mvksdensity – probably the latter

请先登录，再进行评论。