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

The trend-renewal process (TRP) is defined to be a time-transformed renewal process, where the time transformation is given by a trend function λ ( · ) which is similar to the intensity of a non-homogeneous Poisson process (NHPP). A non-parametric maximum likelihood estimator of the trend function o...

Full description

Saved in:
Bibliographic Details
Published in:Reliability engineering & system safety 2007-05, Vol.92 (5), p.575-584
Main Authors: Heggland, Knut, Lindqvist, Bo H.
Format: Article
Language:English
Subjects:
Bootstrapping
Isotonic regression
Non-parametric estimation
Repairable system
Trend-renewal process
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The trend-renewal process (TRP) is defined to be a time-transformed renewal process, where the time transformation is given by a trend function λ ( · ) 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 λ ( · ) 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.
ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2006.05.007