More Complex Models for Random Durations

Abstract

This chapter considers aleatory models that allow for a non-constant rate. Such models are often used in risk assessment for recovery and repair. Three commonly used distributions are treated: Weibull, lognormal, and gamma. Bayesian model checking is covered using posterior predictive checks and information criteria based on a penalized likelihood function. Also covered is the impact of parameter uncertainty on derived quantities, such as nonrecovery probabilities; failure to consider parameter uncertainty can lead to nonconservatively low estimates of such quantities, and thus to overall risk metrics that are nonconservative.