R中威布尔曲线下的子区域着色

# 导入必要的包
library(survival)

# 创建一个威布尔分布对象
weibull_dist <- function(x, shape, scale) {
  return((shape/scale) * (x/scale)^(shape-1) * exp(-(x/scale)^shape))
}

# 设置威布尔分布的形状参数和尺度参数
shape <- 2
scale <- 3

# 计算威布尔分布的概率密度函数
x <- seq(0, 10, by = 0.1)
pdf <- weibull_dist(x, shape, scale)

# 计算威布尔分布的累积分布函数
cdf <- 1 - exp(-((x/scale)^shape))

# 可视化威布尔分布
plot(x, pdf, type = "l", xlab = "x", ylab = "Density", main = "Weibull Distribution")
lines(x, cdf, col = "red")
legend("topright", legend = c("PDF", "CDF"), col = c("black", "red"), lty = 1)

# 导入必要的包
library(survival)

# 创建一个威布尔分布对象
weibull_dist <- function(x, shape, scale) {
  return((shape/scale) * (x/scale)^(shape-1) * exp(-(x/scale)^shape))
}

# 设置威布尔分布的形状参数和尺度参数
shape <- 2
scale <- 3

# 计算威布尔分布的概率密度函数
x <- seq(0, 10, by = 0.1)
pdf <- weibull_dist(x, shape, scale)

# 计算威布尔分布的累积分布函数
cdf <- 1 - exp(-((x/scale)^shape))

# 设置阈值
threshold <- 5

# 找到阈值对应的索引
index <- which(x >= threshold)[1]

# 可视化威布尔分布，并着色区域
plot(x, pdf, type = "l", xlab = "x", ylab = "Density", main = "Weibull Distribution")
lines(x, cdf, col = "red")
polygon(c(x[index:length(x)], rev(x[index:length(x)])), c(pdf[index:length(pdf)], rep(0, length(pdf)-index+1)), col = "gray")
legend("topright", legend = c("PDF", "CDF", paste("Area >= ", threshold)), col = c("black", "red", "gray"), lty = 1)