Kernel-based Estimation of Ageing Intensity Function: Properties and Applications

IF 0.6 Q4 STATISTICS & PROBABILITY

Austrian Journal of Statistics Pub Date : 2023-09-11 DOI:10.17713/ajs.v52i5.1497

R S Rasin, None S M Sunoj, None Rakesh Poduval

引用次数: 0

Abstract

The notion of ageing plays an important role in reliability and survival analysis as it is an inherent property of all systems and products. Jiang, Ji, and Xiao (2003) proposed a new quantitative measure, known as ageing intensity (AI) function, an alternative measureto study the ageing pattern of probability models. In this paper, we propose a nonparametric estimator for ageing intensity function. Asymptotic properties of the estimator are established under suitable regularity conditions. A set of simulation studies are carriedout based on various probability models to examine the performance of estimator and to establish its efficiency over the classical estimator. The usefulness of the estimator is also examined through a real data set.

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基于核的老化强度函数估计:性质与应用

老化的概念在可靠性和生存分析中起着重要作用，因为它是所有系统和产品的固有属性。Jiang, Ji, and Xiao(2003)提出了一种新的定量度量，称为老化强度(AI)函数，这是研究概率模型老化模式的一种替代度量。本文提出了一种老化强度函数的非参数估计方法。在适当的正则性条件下，建立了估计量的渐近性质。在各种概率模型的基础上进行了一系列仿真研究，以检验该估计器的性能，并证明其优于经典估计器。通过一个实际数据集检验了该估计器的有效性。

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

Austrian Journal of Statistics STATISTICS & PROBABILITY-

CiteScore

1.10

自引率

0.00%

发文量

审稿时长

24 weeks

期刊介绍： The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.