Reinforced urns and the subdistribution beta-Stacy process prior for competing risks analysis
Abstract
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.
Cite
@article{arxiv.1811.12304,
title = {Reinforced urns and the subdistribution beta-Stacy process prior for competing risks analysis},
author = {Andrea Arfé and Stefano Peluso and Pietro Muliere},
journal= {arXiv preprint arXiv:1811.12304},
year = {2018}
}
Comments
To appear in the Scandinavian Journal of Statistics