A non-parametric monotone maximum likelihood estimator of time trend for repairable system data

被引:14
作者
Heggland, Knut [1 ]
Lindqvist, Bo H. [1 ]
机构
[1] Norwegian Univ Sci & Technol, Dept Math Sci, N-7491 Trondheim, Norway
关键词
repairable system; trend-renewal process; non-parametric estimation; isotonic regression; bootstrapping;
D O I
10.1016/j.ress.2006.05.007
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The trend-renewal process (TRP) is defined to be a time-transformed renewal process, where the time transformation is given by a trend function lambda((.)) which is similar to the intensity of a non-homogeneous Poisson process (NHPP). A non-parametric maximum likelihood estimator of the trend function of a TRP is obtained under the often natural condition that lambda((.)) is monotone. An algorithm for computing the estimate is suggested and examined in detail in the case where the renewal distribution of the TRP is a Weibull distribution. The case where one has data from several systems is also briefly studied. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:575 / 584
页数:10
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