如何在C中获得足够好的伪随机均匀分布整数进行统计模拟? [英] How to get pseudo-random uniformly distributed integers in C good enough for statistical simulation?

问题描述

我正在编写蒙特卡罗模拟，并且需要大量随机位来生成均匀分布在 {1,2,...,N} 上的整数，其中 N<40.使用 C rand 函数的问题在于，使用标准的 rand % N 技术我会浪费很多非常好的位.生成整数的更好方法是什么?

I'm writing a Monte Carlo simulation and am going to need a lot of random bits for generating integers uniformly distributed over {1,2,...,N} where N<40. The problem with using the C rand function is that I'd waste a lot of perfectly good bits using the standard rand % N technique. What's a better way for generating the integers?

我不需要加密安全的随机数，但我不希望它们歪曲我的结果.另外，我不考虑从 random.org 下载一批解决方案.

I don't need cryptographically secure random numbers, but I don't want them to skew my results. Also, I don't consider downloading a batch of bits from random.org a solution.

推荐答案

rand % N 不起作用；除非 RAND_MAX + 1 是 N 的倍数，否则它会扭曲你的结果.

rand % N does not work; it skews your results unless RAND_MAX + 1 is a multiple of N.

正确的做法是找出小于RAND_MAX的N的最大倍数，然后生成随机数，直到小于该值.只有这样你才应该做模运算.这为您提供了 50% 的最坏情况拒绝率.

A correct approach is to figure out the largest multiple of N that's smaller than RAND_MAX, and then generate random numbers until it's less than that value. Only then should you do the modulo operation. This gives you a worst-case rejection ratio of 50%.

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