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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...
Persistent link: https://www.econbiz.de/10010343915
Bayesian nonparametric inference is a relatively young area of research and it has recently undergone a strong development. Most of its success can be explained by the considerable degree of exibility it ensures in statistical modelling, if compared to parametric alternatives, and by the...
Persistent link: https://www.econbiz.de/10013152997
The present paper provides a review of the results concerning distributional properties of means of random probability measures. Our interest in this topic has originated from inferential problems in Bayesian Nonparametrics. Nonetheless, it is worth noting that these random quantities lay an...
Persistent link: https://www.econbiz.de/10013153000
Persistent link: https://www.econbiz.de/10012297478
Persistent link: https://www.econbiz.de/10005238533
In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently it has been shown that they can also be exploited in species sampling...
Persistent link: https://www.econbiz.de/10009651024
Move-to-front rule is a heuristic updating a list of n items according to requests. Items are required with unknown probabilities (or ppopularities). The induced Markov chain is known to be ergodic [4]. One main problem is the study of the distribution of the search cost defined as the position...
Persistent link: https://www.econbiz.de/10009651025
Persistent link: https://www.econbiz.de/10009651030
The definition of vectors of dependent random probability measures is a topic of interest in applications to Bayesian statistics. They, indeed, represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. In this...
Persistent link: https://www.econbiz.de/10009651075
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...
Persistent link: https://www.econbiz.de/10009651797