RSS Local Group: Catalina Vallejos

Catalina Vallejos, University of Warwick

Thursday 24 October 2013, 1600-1700
A54, Postgraduate Statistics Centre Lecture Theatre

Robust Bayesian methods for survival analysis using rate mixtures of Weibull distributions

Survival models such as the Weibull or log-normal lead to inference that is not robust to the presence of outliers. They also assume that all heterogeneity between individuals can be modelled through covariates. This article considers the use of infinite mixtures of lifetime distributions as a solution for these two issues. This can be interpreted as the introduction of a random effect in the survival distribution. We introduce the family of Rate Mixtures of Weibull distributions, which includes the known Lomax distribution. Bayesian inference under a prior that combines the structure of the Jeffreys' prior and a proper (informative) prior is implemented and the existence of the posterior distribution is verified. In addition, a method for outlier detection based on the mixture structure is proposed. Finally, the analysis is illustrated using real datasets.