问题描述
我要绘制一个二元正态分布的3D表面及其轮廓(可以是任何二元正态分布).我想在图形中使用 persp 和 contour .我在Internet上进行了搜索，但是发现了很多方法.他们中的大多数人已经使用了一些软件包.但是我想以一种使用更少软件包的方式来执行此操作，或者甚至不安装任何软件包(但是，我不知道这是可能的).您能否以二元正态分布为例，向我展示自己的方式?[更少的软件包，更好的解决方案].的确，我希望看到绘制二元正态分布的表面和轮廓的最简单方法.
I am going to plot the 3D surface of a bivariate normal distribution and its contours (it could be any bivariate normal distribution). I want to use persp and contour in my drawing.I searched on the Internet, but I found many ways to do it. Most of them have used some packages. But I would like to do this in a way that uses fewer packages or even without installing any package (however, I do not know it is possible). Could you please show me your own way with an example of a bivariate normal distribution?[Fewer packages, better solution]. Indeed I would like to see the simplest way of drawing a surface and contours of a bivariate normal distribution.
推荐答案
只要您准备编写自己的代码即可在R中完成任何您喜欢的事情而无需使用包.使用 persp 和 contour 仅用几行R代码就可以可视化2d表面，但是生成表面(即创建2d密度)情节，并非无关紧要.
You can do just about anything you like in R without using packages, as long as you are prepared to write your own code to do it. Visualising a 2d surface is possible in just a few lines of R code using persp and contour, but generating the surface (i.e. creating a 2d density plot, is not trivial.
在这里，您可以仅使用 mnormt 包(如注释中所述)生成二维双变量正态分布曲面.对于此示例，我组成了一个虚拟方差-协方差矩阵.
Here is how you can generate a 2d bivariate normal distribution surface using just the mnormt package (as requested in the comments). For this example, I have made up a dummy variance-covariance matrix.
library(mnormt)
x <- seq(-5, 5, 0.25)
y <- seq(-5, 5, 0.25)
mu <- c(0, 0)
sigma <- matrix(c(2, -1, -1, 2), nrow = 2)
f <- function(x, y) dmnorm(cbind(x, y), mu, sigma)
z <- outer(x, y, f)
contour(x, y, z)
persp(x, y, z, theta = -30, phi = 25,
shade = 0.75, col = "gold", expand = 0.5, r = 2,
ltheta = 25, ticktype = "detailed")
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