How to plot bivariate normal distribution with expanding ellipses and add 5%, 25%, 50%, 75% and 95% label in the plot? Thank you!
如何绘制具有扩展椭圆的二元正态分布并在图中添加5％，25％，50％，75％和95％标签？谢谢！
1 个解决方案
#1
1
You can create a contour plot using an R package called mvtnorm.
您可以使用名为mvtnorm的R包创建等高线图。
Let's say you're trying to plot a bivariate normal distribution where mu_x = 1 and mu_y = 1 and variance matrix is c(2,1,1,1). Generate 100 observations for x,y,z. You can create a contour plot for this scenario as such:
假设您正在尝试绘制双变量正态分布，其中mu_x = 1且mu_y = 1且方差矩阵为c（2,1,1,1）。为x，y，z生成100个观测值。您可以为此方案创建等高线图：
library(mvtnorm)
x.points <- seq(-3,3,length.out=100)
y.points <- x.points
z <- matrix(0,nrow=100,ncol=100)
mu <- c(1,1)
sigma <- matrix(c(2,1,1,1),nrow=2)
for (i in 1:100) {
for (j in 1:100) {
z[i,j] <- dmvnorm(c(x.points[i],y.points[j]),
mean=mu,sigma=sigma)
}
}
contour(x.points,y.points,z)
#1
1
You can create a contour plot using an R package called mvtnorm.
您可以使用名为mvtnorm的R包创建等高线图。
Let's say you're trying to plot a bivariate normal distribution where mu_x = 1 and mu_y = 1 and variance matrix is c(2,1,1,1). Generate 100 observations for x,y,z. You can create a contour plot for this scenario as such:
假设您正在尝试绘制双变量正态分布，其中mu_x = 1且mu_y = 1且方差矩阵为c（2,1,1,1）。为x，y，z生成100个观测值。您可以为此方案创建等高线图：
library(mvtnorm)
x.points <- seq(-3,3,length.out=100)
y.points <- x.points
z <- matrix(0,nrow=100,ncol=100)
mu <- c(1,1)
sigma <- matrix(c(2,1,1,1),nrow=2)
for (i in 1:100) {
for (j in 1:100) {
z[i,j] <- dmvnorm(c(x.points[i],y.points[j]),
mean=mu,sigma=sigma)
}
}
contour(x.points,y.points,z)