正态分布-R语言

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dnorm(x, mean = 0, sd = 1, log = FALSE)
pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
qnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
rnorm(n, mean = 0, sd = 1)

//-----------------------------
dnorm 正态分布的概率密度函数值,即 pdf
dnorm(0,mean = 0, sd = 1.5, log = FALSE)
0.2659615
dnorm(0,mean = 0, sd = 1.0, log = FALSE)
0.3989423
dnorm(0,mean = 0, sd = .5, log = FALSE)
0.7978846

//-------------------------------
pnorm 正态分布的概率分布函数，即 cdf 下列计算3σ
pnorm(1, mean = 0, sd = 1, log = FALSE) - pnorm(-1, mean = 0, sd = 1, log = FALSE)
0.6826895
pnorm(2, mean = 0, sd = 1, log = FALSE) - pnorm(-2, mean = 0, sd = 1, log = FALSE)
0.9544997
pnorm(3, mean = 0, sd = 1, log = FALSE) - pnorm(-3, mean = 0, sd = 1, log = FALSE)
0.9973002

//-----------------------------------
qnorm 正态分布的概率分布函数的反函数，根据概率分布求分位数
qnorm(0.0026998/2+0.997302, mean = 0, sd = 1, log = FALSE)
3.000406
qnorm(0.0026998/2, mean = 0, sd = 1, log = FALSE)
-3

//-------------------------------------
rnorm 正态分布的随机变量产生函数
a.random <- rnorm(100, mean = 0, sd = 1)
a.random <- sort(a.random)
pnorm(a.random,0,1)

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