On optimal joint prediction of order statistics

IF 1.2 4区数学 Q2 STATISTICS & PROBABILITY

Statistics Pub Date : 2023-08-27 DOI:10.1080/02331888.2023.2249572

N. Balakrishnan, R. Mukerjee

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.

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序统计量的最优联合预测

本文讨论了基于位置尺度族的ii型截尾样本的无观测阶统计量的联合估计和预测问题。利用洛厄纳阶的概念，我们简化了前面的推导，并在此过程中加强了一些已有的结果。然后，我们研究了方法的效率，最后检查了要观察的最优阶统计量的确定以及非线性预测器的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics 数学-统计学与概率论

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

12 months

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.