Computation of distributions of statistics by means of Markov chains

IF 0.3 Q4 MATHEMATICS, APPLIED Discrete Mathematics and Applications Pub Date : 2022-08-01 DOI:10.1515/dma-2022-0024
A. M. Zubkov, M. Filina
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引用次数: 0

Abstract

Abstract An approach to the construction of efficient algorithms for the exact computation of distributions of statistics by means of the Markov chains is described. The Pearson statistic, the number of empty cells for random allocations of particles, and the Kolmogorov – Smirnov statistic are considered as examples. Possibilities of extending the approach are discussed, in particular to the computation of the joint distributions of statistics.
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用马尔可夫链计算统计分布
摘要本文描述了利用马尔可夫链构造精确计算统计分布的有效算法的方法。Pearson统计量、随机分配粒子的空单元数和Kolmogorov - Smirnov统计量作为例子。讨论了扩展该方法的可能性,特别是统计量联合分布的计算。
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来源期刊
CiteScore
0.60
自引率
20.00%
发文量
29
期刊介绍: The aim of this journal is to provide the latest information on the development of discrete mathematics in the former USSR to a world-wide readership. The journal will contain papers from the Russian-language journal Diskretnaya Matematika, the only journal of the Russian Academy of Sciences devoted to this field of mathematics. Discrete Mathematics and Applications will cover various subjects in the fields such as combinatorial analysis, graph theory, functional systems theory, cryptology, coding, probabilistic problems of discrete mathematics, algorithms and their complexity, combinatorial and computational problems of number theory and of algebra.
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