{"title":"On optimal joint prediction of order statistics","authors":"N. Balakrishnan, R. Mukerjee","doi":"10.1080/02331888.2023.2249572","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss the joint estimation and prediction of unobserved order statistics based on a Type-II censored sample from a location-scale family. Using the concept of Loewner order, we simplify the derivations made earlier, and also strengthen in the process some of the existing results. We then study the efficiency of the methods and finally examine the determination of optimal number of order statistics to be observed as well as the performance of non-linear predictors.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"13 1","pages":"1239 - 1250"},"PeriodicalIF":1.2000,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02331888.2023.2249572","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we discuss the joint estimation and prediction of unobserved order statistics based on a Type-II censored sample from a location-scale family. Using the concept of Loewner order, we simplify the derivations made earlier, and also strengthen in the process some of the existing results. We then study the efficiency of the methods and finally examine the determination of optimal number of order statistics to be observed as well as the performance of non-linear predictors.
期刊介绍：
Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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