来自三角分布的随机样本：R

Question

我想从具有三个参数的三角分布生成数字：a、b、c，其中 c 在我的例子中定义为 (a+b)/2。假设我有一个向量 x:

x <- c(1,-1,2,-2,3,-3,4,-4,5,-5,11,-11,12,-12,13,-13)

我想生成与向量 x 中的负数一样多的新值。因此，我可以进一步用三角分布生成的数字替换负值。

library(triangle)
c = abs(x[x<0])/2
sample <- rtriangle(length(a[which(a<0)]), 0, abs(x[x<0]),c)

显然这不起作用，因为我收到一条警告消息：

Warning messages: 1: In if (a > c | b < c) return(rep(NaN, times = n)) : the condition has length > 1 and only the first element will be used 2: In if (a != c) { : the condition has length > 1 and only the first element will be used 3: In p[i] * (b - a) : longer object length is not a multiple of shorter object length 4: In p[i] <- a + sqrt(p[i] * (b - a) * (c - a)) : number of items to replace is not a multiple of replacement length 5: In (1 - p[j]) * (b - a) : longer object length is not a multiple of shorter object length 6: In p[j] <- b - sqrt((1 - p[j]) * (b - a) * (b - c)) : number of items to replace is not a multiple of replacement length

Answer 1

由于 rtriangle 不将向量作为输入，您可以使用 sapply 创建一个向量来评估向量的每个元素，如下所示：

x <- c(1,-1,2,-2,3,-3,4,-4,5,-5,11,-11,12,-12,13,-13)

library("triangle")

sample = sapply(abs(x[x<0]), function(x){ rtriangle(1,0,x,x/2) })

> sample
[1] 0.6514940 0.6366981 1.8598445 0.9866790 1.7517438 2.9444719 4.1537113 2.2315813

您将获得 8 种不同三角分布的随机样本。

来自三角分布的随机样本：R

A random sample from triangular distribution: R

simulation

statistics

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