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Competing risks models for a repairable system subject to several failuremodes are discussed. Under minimal repair, it is assumed that each failure modehas a power law intensity. An orthogonal reparametrization is used to obtain anobjective Bayesian prior which is invariant under relabelling of the failuremodes. The resulting posterior is a product of gamma distributions and hasappealing properties: one-to-one invariance, consistent marginalization andconsistent sampling properties. Moreover, the resulting Bayes estimators haveclosed-form expressions and are naturally unbiased for all the parameters ofthe model. The methodology is applied in the analysis of (i) a previouslyunpublished dataset about recurrent failure history of a sugarcane harvesterand (ii) records of automotive warranty claims introduced in [1]. A simulationstudy was carried out to study the efficiency of the methods proposed.

Objective Bayesian Inference for Repairable System Subject to Competing Risks