{"title":"多元规模偏差抽样下的推断。","authors":"A Batsidis, G Tzavelas, P Economou","doi":"10.1080/02664763.2025.2451972","DOIUrl":null,"url":null,"abstract":"<p><p>The present research deals with statistical inference for the expectation of a function of a random vector based on biased samples. After highlighting with the help of a motivating example the need for conducting this study, using the concept of multivariate weighted distributions, a consistent and asymptotically normally distributed estimator is proposed and utilized for developing statistical inference. A Monte Carlo study is carried out to examine the performance of the estimator proposed. Finally, the analysis of a real-world data set illustrates the benefits of using the proposed methods for statistical inference.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"52 10","pages":"1968-1983"},"PeriodicalIF":1.1000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12320264/pdf/","citationCount":"0","resultStr":"{\"title\":\"Inference under multivariate size-biased sampling.\",\"authors\":\"A Batsidis, G Tzavelas, P Economou\",\"doi\":\"10.1080/02664763.2025.2451972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The present research deals with statistical inference for the expectation of a function of a random vector based on biased samples. After highlighting with the help of a motivating example the need for conducting this study, using the concept of multivariate weighted distributions, a consistent and asymptotically normally distributed estimator is proposed and utilized for developing statistical inference. A Monte Carlo study is carried out to examine the performance of the estimator proposed. Finally, the analysis of a real-world data set illustrates the benefits of using the proposed methods for statistical inference.</p>\",\"PeriodicalId\":15239,\"journal\":{\"name\":\"Journal of Applied Statistics\",\"volume\":\"52 10\",\"pages\":\"1968-1983\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-01-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12320264/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/02664763.2025.2451972\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02664763.2025.2451972","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Inference under multivariate size-biased sampling.
The present research deals with statistical inference for the expectation of a function of a random vector based on biased samples. After highlighting with the help of a motivating example the need for conducting this study, using the concept of multivariate weighted distributions, a consistent and asymptotically normally distributed estimator is proposed and utilized for developing statistical inference. A Monte Carlo study is carried out to examine the performance of the estimator proposed. Finally, the analysis of a real-world data set illustrates the benefits of using the proposed methods for statistical inference.
期刊介绍:
Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.