计算累积二项式概率时R中的奇怪精度问题 [英] Strange precision issues in R when computing cumulative binomial probability

问题描述

使用此代码时，我遇到了一些奇怪的问题：

I've been running into some weird problems when using this code:

positions<-c(58256)
occurrencies<-c(30)
frequency<-c(11/5531777)
length<-c(4)

prob<-c(0)
for(i in 0:(occurrencies-1))
{
  pow<-frequency^i
  pow1<-(1-frequency)^(positions-i)
  bin<-choose(positions, i)
  prob<<-prob+(bin*pow*pow1)
}

此for循环的每次迭代应计算在给定频率下事件发生次数 i 的二项式概率。每次迭代还会汇总结果。这应该导致 prob 变量永远不会超过1，但是在7次左右的循环迭代之后，一切都陷入地狱，而 prob 超越1。

Each iteration of this for loop should calculate the binomial probability that, i number of occurrences of the event occur given the frequency. Each iteration also sums up the result. This should result in the prob variable never exceeding 1, but after 7 or so for loop iterations, everything goes to hell and prob excedes 1.

我认为这可能是精度数字的问题，因此我尝试使用 Rmpfr 但无济于事-仍然存在相同的问题。

I thought it might be a question of precision digits, so i tried using Rmpfr but to no avail- the same problem persisted.

我想知道是否有任何技巧或软件包可以克服这种情况，或者我是否坚持下去。

I was wondering if there are any tips or packages to overcome this situation, or if I'm stuck with this.

推荐答案

按照Ben Bolker的建议看？pbinom

Following Ben Bolker's advice to see ?pbinom

pbinom(q = occurencies, size = positions, prob = frequency, lower.tail = FALSE)

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