{"title":"A Generalised Matching Distribution for the Problem of Coincidences","authors":"Ben O’Neill","doi":"10.1007/s11009-023-10067-6","DOIUrl":null,"url":null,"abstract":"<p>This paper examines the classical matching distribution arising in the “problem of coincidences”. We generalise the classical matching distribution with a preliminary round of allocation where items are correctly matched with some fixed probability, and remaining non-matched items are allocated using simple random sampling without replacement. Our generalised matching distribution is a convolution of the classical matching distribution and the binomial distribution. We examine the properties of this latter distribution and show how its probability functions can be computed. We also show how to use the distribution for matching tests and inferences of matching ability.</p>","PeriodicalId":18442,"journal":{"name":"Methodology and Computing in Applied Probability","volume":"17 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methodology and Computing in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11009-023-10067-6","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper examines the classical matching distribution arising in the “problem of coincidences”. We generalise the classical matching distribution with a preliminary round of allocation where items are correctly matched with some fixed probability, and remaining non-matched items are allocated using simple random sampling without replacement. Our generalised matching distribution is a convolution of the classical matching distribution and the binomial distribution. We examine the properties of this latter distribution and show how its probability functions can be computed. We also show how to use the distribution for matching tests and inferences of matching ability.
期刊介绍:
Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics.
The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests:
-Algorithms-
Approximations-
Asymptotic Approximations & Expansions-
Combinatorial & Geometric Probability-
Communication Networks-
Extreme Value Theory-
Finance-
Image Analysis-
Inequalities-
Information Theory-
Mathematical Physics-
Molecular Biology-
Monte Carlo Methods-
Order Statistics-
Queuing Theory-
Reliability Theory-
Stochastic Processes