In this paper we introduce the subdistribution beta-Stacy process, a novel Bayesian nonparametric process prior for subdistribution functions useful for the analysis of competing risks data. In particular, we i) characterize this process from a predictive perspective by means of an urn model with reinforcement, ii) show that it is conjugate with respect to right-censored data, and iii) highlight its relations with other prior processes for competing risks data. Additionally, we consider the subdistribution beta-Stacy process prior in a nonparametric regression model for competing risks data which, contrary to most others available in the literature, is not based on the proportional hazards assumption.
|Rivista||Scandinavian Journal of Statistics|
|Stato di pubblicazione||Pubblicato - 2018|
- Bayesian Nonparametrics
- Competing Risks
- Subdistribution beta-Stacy
- Urn Process