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Non-Recursive Computation of the Probability of More than Two People Having the Same Birthday

机译:非递归计算有两个以上有同一个生日的人的概率

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We address a well known problem of computer science, the problem of computing the probability that a given number of people m > 1 have the same birthday from among the members of a larger set of cardinality n ≥ m. The solution to this problem for m = 2 is well known and is usually referred to as the 'birthday surprise probability'. A solution for m = 3 is also known and appears in the 2004 paper by DasGupta [The matching, birthday and the strong birthday problem: a contemporary review, Journal of Statistical Planning and Inference]. Further approximations to the solution of the related problem of computing the minimum number of people to interview until m people with the same birthday are found are presented in the seminal work by Klamkin and Newman [Extensions on the birthday surprise, Journal of Combinatorial Theory, 1967]. In this paper we present a new non-recursive approximation for the birthday probability applicable to any value of m > 1, which yields results that are experimentally proven accurate under the assumption that the number of birthdays is significantly larger than the number of people. Our expression is easy to compute, non-recursive, and applicable to values of m that can be arbitrarily larger than 2 or 3. We verify the validity of our result computing the birthday probability for different values of m, over billions of sets of random values generated using the Intel RDRAND hardware random number generation instruction. Our solution is based on a novel tree-based description of the event space which, if used, allows for the computation of the birthday probability efficiently and without involving recursions or multinomial distributions.
机译:我们解决了计算机科学的众所周知的问题,计算给定数量的人1的概率的问题与较大一组基数N≥M的成员中具有相同的生日。对于M = 2的这个问题的解决方案是众所周知的,并且通常称为“生日惊喜概率”。 M = 3的解决方案也是已知的,并在2004纸上出现了Dasgupta [匹配,生日和生日问题:当代审查,统计规划和推理。进一步近似于计算最少人数的相关问题,直到找到具有同一个生日的人在麦金金和纽曼的开创性工作中介绍了[纽曼的延伸,1967年组合理论杂志。 ]。在本文中,我们向适用于M> 1的任何值的生日概率提出了一种新的非递归近似,这产生了在假设生日数量明显大于人数的假设下进行了实验证明的结果。我们的表达易于计算,非递归,并且适用于可以任意大于2或3的M的值。我们验证了我们的结果计算不同值M的生日概率,超过数十亿种随机使用英特尔RDRAND硬件随机数生成指令生成的值。我们的解决方案基于事件空间的基于树的基于树的描述,如果使用,则允许有效地计算生日概率,而不涉及递减或多项分布。

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