[英]How do a perform a weighted, 2d kernel density estimation in R?
I would like to produce a kernel density estimation in R, and am somewhat bamboozled by all the different packages. 我想在R中产生内核密度估计,并且对所有不同的软件包都有些困惑。 I need to be able to: 我需要能够:
How would you go about this? 您将如何处理? Bonus points for a code snippet. 代码段的奖励积分。
Off course there's a number of packages. 当然,这里有很多包裹。 You should first decide which 2D kernel estimate you want. 你应该先决定哪些 2D核估计你想要的。 In the fields package you have a function smooth.2d, and you have the wonderful package of Brian Ripley, KernSmooth. 在fields程序包中,您具有函数smooth.2d,并且您具有KernSmooth的Brian Ripley出色的程序包。 The extra points for the code snippets you can give to the help files, I ain't going to copy them. 您可以为帮助文件提供的代码段的额外要点,我不会复制它们。
For these kind of questions, also try www.rseek.org . 对于此类问题,也请尝试www.rseek.org 。
另请参阅ks程序包和多变量内核密度估计中的精美图片。
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