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Nonparametric priors for vectors of survival functions

Author

Listed:
  • Ilenia Epifani
  • Antonio Lijoi

Abstract

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 Lévy 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 Lévy measures.

Suggested Citation

  • Ilenia Epifani & Antonio Lijoi, 2009. "Nonparametric priors for vectors of survival functions," Carlo Alberto Notebooks 132, Collegio Carlo Alberto.
    • Handle: RePEc:cca:wpaper:132
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