{"title":"负相关随机变量部分和最大值的完全q矩收敛性及其在EV回归模型中的应用*","authors":"Fen Jiang, Miaomiao Wang, Xuejun Wang","doi":"10.1080/15326349.2022.2112604","DOIUrl":null,"url":null,"abstract":"Abstract In this article, we prove the complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables under some general conditions. The results obtained in this article are extensions of previous studies for -negatively associated random variables. In addition, we investigate the strong consistency of the least squares estimator in the simple linear errors-in-variables model based on -negatively associated random variables, and provide some simulations to assess the finite sample performance of the theoretical results.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":"39 1","pages":"448 - 468"},"PeriodicalIF":0.5000,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables and its application to the EV regression model*\",\"authors\":\"Fen Jiang, Miaomiao Wang, Xuejun Wang\",\"doi\":\"10.1080/15326349.2022.2112604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In this article, we prove the complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables under some general conditions. The results obtained in this article are extensions of previous studies for -negatively associated random variables. In addition, we investigate the strong consistency of the least squares estimator in the simple linear errors-in-variables model based on -negatively associated random variables, and provide some simulations to assess the finite sample performance of the theoretical results.\",\"PeriodicalId\":21970,\"journal\":{\"name\":\"Stochastic Models\",\"volume\":\"39 1\",\"pages\":\"448 - 468\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2022-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stochastic Models\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/15326349.2022.2112604\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Models","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/15326349.2022.2112604","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables and its application to the EV regression model*
Abstract In this article, we prove the complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables under some general conditions. The results obtained in this article are extensions of previous studies for -negatively associated random variables. In addition, we investigate the strong consistency of the least squares estimator in the simple linear errors-in-variables model based on -negatively associated random variables, and provide some simulations to assess the finite sample performance of the theoretical results.
期刊介绍:
Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.