June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
Content preview from R 语言经典实例（原书第 2 版）
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8.10.4 另请参阅
确定数据集的分位数与确定分布的分位数不同——参见 9.5 节。
8.11 绘制密度函数
8.11.1 问题
你需要绘制概率分布的密度函数。
8.11.2 解决方案
在一定范围内定义一个向量 x。将分布的密度函数应用于 x，然后绘制结果。如果 x 是
你关心的绘图范围上的点向量，则使用 d_____ 密度函数之一（例如对数正态分布的
dlnorm 或正态分布的 dnorm）计算密度：
dens <- data.frame(x = x,
y = d_____(x))
ggplot(dens, aes(x, y)) + geom_line()
以下是绘制区间
-
3 到 +3 的标准正态分布的具体示例：
library(ggplot2)
x <- seq(-3, +3, 0.1)
dens <- data.frame(x = x, y = dnorm(x))
ggplot(dens, aes(x, y)) + geom_line()
图 8-1 显示了平滑密度函数。
0.4
0.3
0.2
0.1
0.0
y
-
2 20
x
图 8-1：平滑密度函数
概率
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8.11.3 讨论
所有 R 的内置概率分布都包括密度函数。对于一个特定的密度，函数名称是在分布名称前
面加上“d”。正态分布的密度函数是 ...
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