{"title":"随机加法矩阵的不平衡多拉缸ⅱ","authors":"Rafik Aguech, Wissem Jedidi, Olfa Selmi","doi":"10.1080/23799927.2023.2262433","DOIUrl":null,"url":null,"abstract":"AbstractIn this paper, we give some results about a multi-drawing urn with random addition matrix. The process that we study is described as: at stage n≥1, we pick out at random m balls, say k white balls and m−k black balls. We inspect the colours and then we return the balls, according to a predefined replacement matrix, together with (m−k)Xn white balls and kYn black balls. Here, we extend the classical assumption that the random variables (Xn,Yn) are bounded and i.i.d. We prove a strong law of large numbers and a central limit theorem on the proportion of white balls for the total number of balls after n draws under the following more general assumptions: (i) a finite second-order moment condition in the i.i.d. case; (ii) regular variation type for the first and second moments in the independent case.Keywords: Central limit theoremmartingaleregular variationunbalanced urnstochastic algorithmstrong law of large numbers AcknowledgementsThe authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).","PeriodicalId":37216,"journal":{"name":"International Journal of Computer Mathematics: Computer Systems Theory","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unbalanced multi-drawing urn with random addition matrix II\",\"authors\":\"Rafik Aguech, Wissem Jedidi, Olfa Selmi\",\"doi\":\"10.1080/23799927.2023.2262433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractIn this paper, we give some results about a multi-drawing urn with random addition matrix. The process that we study is described as: at stage n≥1, we pick out at random m balls, say k white balls and m−k black balls. We inspect the colours and then we return the balls, according to a predefined replacement matrix, together with (m−k)Xn white balls and kYn black balls. Here, we extend the classical assumption that the random variables (Xn,Yn) are bounded and i.i.d. We prove a strong law of large numbers and a central limit theorem on the proportion of white balls for the total number of balls after n draws under the following more general assumptions: (i) a finite second-order moment condition in the i.i.d. case; (ii) regular variation type for the first and second moments in the independent case.Keywords: Central limit theoremmartingaleregular variationunbalanced urnstochastic algorithmstrong law of large numbers AcknowledgementsThe authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).\",\"PeriodicalId\":37216,\"journal\":{\"name\":\"International Journal of Computer Mathematics: Computer Systems Theory\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Mathematics: Computer Systems Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23799927.2023.2262433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Mathematics: Computer Systems Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23799927.2023.2262433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Unbalanced multi-drawing urn with random addition matrix II
AbstractIn this paper, we give some results about a multi-drawing urn with random addition matrix. The process that we study is described as: at stage n≥1, we pick out at random m balls, say k white balls and m−k black balls. We inspect the colours and then we return the balls, according to a predefined replacement matrix, together with (m−k)Xn white balls and kYn black balls. Here, we extend the classical assumption that the random variables (Xn,Yn) are bounded and i.i.d. We prove a strong law of large numbers and a central limit theorem on the proportion of white balls for the total number of balls after n draws under the following more general assumptions: (i) a finite second-order moment condition in the i.i.d. case; (ii) regular variation type for the first and second moments in the independent case.Keywords: Central limit theoremmartingaleregular variationunbalanced urnstochastic algorithmstrong law of large numbers AcknowledgementsThe authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Deanship of Scientific Research at King Saud University for funding their Research group No. (RG-1441-317).