Authors: Müller, Christine H.
Szugat, Sebastian
Maurer, Reinhard
Title: Simulation free prediction intervals for a state dependent failure process using accellerated lifetime experiments
Language (ISO): en
Abstract: We consider the problem of constructing prediction intervals for the time point at which a given number of components of a system exposed to degradation fails. The failure process with respect to the failure times of the components is modeled by a state dependent point process which is an alternative to the nonhomogeneous Poisson process often used in failure analysis. Several failure processes observed at different usually higher stress conditions are incorporated by a link function. Two new simulation- free prediction intervals are proposed. One is constructed with the method and the implicit function theorem applied to the hypoexponential distribution and does not need the construction of confidence sets for the unknown parameters. The other is based on data depth using a recent result for constructing outlier robust confidence sets for general regression. The two new methods are compared with two methods based on classical confidence sets for generalized linear models. The comparison is done by leave-one-out analysis of data coming from failure processes observed at prestressed concrete beams exposed to different cyclic loading where the time points of breaking tension wires were reported.
Subject Headings: point process
data depth
hypoexponential distribution
birth process
Poisson process
Issue Date: 2016
Appears in Collections:Sonderforschungsbereich (SFB) 823

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