ABSTRACT
Mean times to failure are fundamental indicators in reliability and related fields where stochastic processes are used to describe random, real-life systems. Here we focus on the conditional mean time to failure defined in a semi-Markov context. A discrete time semi-Markov model with discrete state space is employed, which allows for realistic description of systems under risk. Our main objective is to estimate the conditional mean time to failure and provide asymptotic properties of its empirical estimator. Consistency and asymptotic normality results are provided and are validated numerically. Our methodology is tested in real and simulated wind data and indicators associated with the wind energy production are estimated.
Acknowledgements
They would like to thank EREN group for providing the data used in this paper. They also thank M. Hamdaoui for fruitful discussions and assistance.
Disclosure statement
No potential conflict of interest was reported by the authors.