{"title":"生成小随机样本的算法","authors":"Vincent A. Cicirello","doi":"10.1002/spe.3379","DOIUrl":null,"url":null,"abstract":"We present algorithms for generating small random samples without replacement. We consider two cases. We present an algorithm for sampling a pair of distinct integers, and an algorithm for sampling a triple of distinct integers. The worst‐case runtime of both algorithms is constant, while the worst‐case runtimes of common algorithms for the general case of sampling elements from a set of increase with . Java implementations of both algorithms are included in the open source library .","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":"16 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algorithms for generating small random samples\",\"authors\":\"Vincent A. Cicirello\",\"doi\":\"10.1002/spe.3379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present algorithms for generating small random samples without replacement. We consider two cases. We present an algorithm for sampling a pair of distinct integers, and an algorithm for sampling a triple of distinct integers. The worst‐case runtime of both algorithms is constant, while the worst‐case runtimes of common algorithms for the general case of sampling elements from a set of increase with . Java implementations of both algorithms are included in the open source library .\",\"PeriodicalId\":21899,\"journal\":{\"name\":\"Software: Practice and Experience\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software: Practice and Experience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/spe.3379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software: Practice and Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/spe.3379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present algorithms for generating small random samples without replacement. We consider two cases. We present an algorithm for sampling a pair of distinct integers, and an algorithm for sampling a triple of distinct integers. The worst‐case runtime of both algorithms is constant, while the worst‐case runtimes of common algorithms for the general case of sampling elements from a set of increase with . Java implementations of both algorithms are included in the open source library .
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