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Epifani, Ilenia
Lijoi, Antonio
Year of Publication: 
Series/Report no.: 
Quaderni di Dipartimento 098
The paper proposes a new nonparametric prior for two–dimensional vectors of survival functions (S1, S2). The definition we introduce is based on the notion of L´evy copula and it will be used to model, in a nonparametric Bayesian framework, two–sample survival data. Such an application will yield a natural extension of the more familiar neutral to the right process of Doksum (1974) adopted for drawing inferences on single survival functions. We, then, obtain a description of the posterior distribution of (S1, S2), conditionally on possibly right–censored data. As a by–product of our analysis, we find out that the marginal distribution of a pair of observations from the two samples coincides with the Marshall–Olkin or the Weibull distribution according to specific choices of the marginal L´evy measures.
Bayesian nonparametrics
Completely random measures
Dependent stable processes
L´evy copulas
Posterior distribution
Right–censored data
Survival function
Document Type: 
Working Paper

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