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Detecting change in a hazard regression model with right-censoring. (English) Zbl 1156.62073

Summary: The hazard function plays an important role in survival analysis and reliability, since it quantifies the instantaneous failure rate of an individual at a given time point \(t\), given that this individual has not failed before \(t\). In some applications, abrupt changes in the hazard function are observed, and it is of interest to detect the location of such a change.
We consider testing of existence of a change in the parameters of an exponential regression model, based on a sample of right-censored survival times and the corresponding covariates. Likelihood ratio type tests are proposed and non-asymptotic bounds for the type II error probability are obtained. When the tests lead to acceptance of a change, estimators for the location of the change are proposed. Non-asymptotic upper bounds of the underestimation and overestimation probabilities are obtained. A short simulation study illustrates these results.

MSC:

62N05 Reliability and life testing
62N03 Testing in survival analysis and censored data
62N01 Censored data models
62N02 Estimation in survival analysis and censored data
62J99 Linear inference, regression
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