{"title":"elnqd随机变量的新的集中不等式和完全收敛，并应用于由elnqd误差产生的线性模型","authors":"FATMA MOUSSAOUI, SAMIR BENAISSA","doi":"10.46939/j.sci.arts-23.3-a17","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce the concept of extended linear negative quadrant dependence (ELNQD, in short). We establish a new concentration inequalities and complete convergence for the distribution of sums of extended linear negative quadrant dependent random variables. Using these inequalities for proved the complete convergence of first autoregressive processes model generated by identically distributed ELNQD errors.","PeriodicalId":54169,"journal":{"name":"Journal of Science and Arts","volume":"43 1","pages":"0"},"PeriodicalIF":0.3000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NEW CONCENTRATION INEQUALITIES AND COMPLETE CONVERGENCE FOR ELNQD RANDOM VARIABLES WITH APPLICATION TO LINEAR MODELS GENERATED BY ELNQD ERRORS\",\"authors\":\"FATMA MOUSSAOUI, SAMIR BENAISSA\",\"doi\":\"10.46939/j.sci.arts-23.3-a17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce the concept of extended linear negative quadrant dependence (ELNQD, in short). We establish a new concentration inequalities and complete convergence for the distribution of sums of extended linear negative quadrant dependent random variables. Using these inequalities for proved the complete convergence of first autoregressive processes model generated by identically distributed ELNQD errors.\",\"PeriodicalId\":54169,\"journal\":{\"name\":\"Journal of Science and Arts\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Science and Arts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46939/j.sci.arts-23.3-a17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science and Arts","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46939/j.sci.arts-23.3-a17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
NEW CONCENTRATION INEQUALITIES AND COMPLETE CONVERGENCE FOR ELNQD RANDOM VARIABLES WITH APPLICATION TO LINEAR MODELS GENERATED BY ELNQD ERRORS
In this paper, we introduce the concept of extended linear negative quadrant dependence (ELNQD, in short). We establish a new concentration inequalities and complete convergence for the distribution of sums of extended linear negative quadrant dependent random variables. Using these inequalities for proved the complete convergence of first autoregressive processes model generated by identically distributed ELNQD errors.
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