另一个趋势更新过程的非参数估计

Q4 Decision Sciences

Journal of the Operations Research Society of Japan Pub Date : 2016-10-01 DOI:10.15807/JORSJ.59.312

Yasuhiro Saito, T. Dohi

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引用次数: 0

摘要

趋势更新过程以计数过程和更新过程为特征，二者通过趋势函数相互转化，是一般修复模型的一个子类。本文提出了另一种趋势更新过程的非参数估计方法，其中更新过程中故障率函数的形式未知。Heggland和Lindqvist(2007)将其视为非参数单调极大似然估计量的对偶方法，并在趋势(强度)函数形式未知的假设下补充了他们的结果。通过仿真实验验证了非参数估计方法的有效性，并将其应用于可修系统的现场数据分析。

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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ANOTHER LOOK AT NONPARAMETRIC ESTIMATION FOR TREND RENEWAL PROCESSES

A trend renewal process is characterized by a counting process and a renewal process which are mutually transformed with each other by a trend function, and plays a significant role to represent a sub-class of general repair models. In this paper we develop another nonparametric estimation method for trend renewal processes, where the form of failure rate function in the renewal process is unknown. It is regarded as a dual approach for the nonparametric monotone maximum likelihood estimator by Heggland and Lindqvist (2007) and complements their result under the assumption that the form of trend (intensity) function is unknown. We validate our nonparametric estimator through simulation experiments and apply to a field data analysis of a repairable system.

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来源期刊

Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学

CiteScore

0.70

自引率

0.00%

发文量

审稿时长

12 months

期刊介绍： The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.