Ping Shing Chan

We discuss the optimal allocation problem in a multi-level accelerated life testing experiment under Type-I censoring when an exponential regression model is used for statistical analysis. We derive the expected Fisher information, and the asymptotic variance-covariance matrix of the maximum likelihood estimators. D-optimality is used to determine the optimal allocations. An algorithm is given to find the optimal allocation. A numerical example is used for illustration. The optimal allocations depends on the model parameters and the sensitivity of the optimal allocations due to the mis-specification of the model parameters is studied.

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**Keywords:** accelerated life testing; exponential regression; optimal design; type I censoring

**Biography:** Prof. Chan is an associate Professor of Department of Statistics, The Chinese University of Hong Kong. He is an elected member of ISI.