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Title: On dynamic modelling in reliability theory Authors:  Vlad Barbu - Universite de Rouen (France)
Alexandros Karagrigoriou - University of The Aegean (Greece) [presenting]
Andreas Makrides - Universite de Rouen (France)
Abstract: The focus is on a general class of distributions for independent not necessarily identically distributed (inid) random variables, closed under extrema, that includes a number of discrete and continuous distributions like the Geometric, Exponential, Weibull or Pareto. The scale parameter involved in this class of distributions is assumed to be time varying with several possible modeling options proposed. Such a modelling setting is of particular interest in reliability and survival analysis for describing the time to event or failure. The maximum likelihood estimation of the parameters is addressed, and the asymptotic properties of the estimators are discussed. We provide real and simulated examples, and we explore the accuracy of the estimating procedure, as well as the performance of classical model selection criteria in choosing the correct model among a number of competing models for the time-varying parameters of interest.