Semiparametric inference for an extended geometric failure rate reduction model

被引：3

作者：

Dauxois, J. -Y. ^{[1
]}

Gasmi, S. ^{[2
]}

Gaudoin, O. ^{[3
]}

机构：

[1] Univ Toulouse, UMR5279, Inst Math Toulouse, CNRS,INSA, F-31077 Toulouse, France

[2] Univ Tunis, ENSIT, OMAD, Bab Menara 1008, Tunisia

[3] Univ Grenoble Alpes, CNRS, Grenoble INP, LJK, F-38000 Grenoble, France

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2019年 / 199卷

关键词：

Asymptotic properties; Imperfect repair; Maintenance efficiency; Reliability; Repairable systems; Simulation study; Statistical inference; REPAIRABLE SYSTEMS; IMPERFECT REPAIR; MAINTENANCE;

D O I：

10.1016/j.jspi.2018.05.002

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The aim of this paper is twofold. First a new imperfect maintenance model is introduced. This model is an extension of Finkelstein's Geometric Failure Rate Reduction model, using the modification proposed by Bordes and Mercier for extending the Geometric Process. Second, based on the observation of several systems, the semiparametric inference in this model is studied. Estimators of the euclidean and functional model parameters are derived and their asymptotic normality is proved. A simulation study is carried out to assess the behavior of these estimators for samples of small or moderate size. Finally, an application on a real dataset is presented. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：14 / 28

页数：15

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