Titlebook: Nonparametric Bayesian Inference; Contributions by Jea Jean-Pierre Florens,Michel Mouchart Book 2024 The Editor(s) (if applicable) and The

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https://doi.org/10.1007/978-3-031-61329-6Bayesian nonparemetric models; Dirichlet processes; Bayesian moment estimation; Duration models; Mathema

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Weak Conditional Independence and Relative Invariance in Bayesian Statisticsssary conditions for the existence of a well-defined “marginal-conditional” decomposition (actually, a desintegration) or a .-finite measure. This framework is then used to handle invariance arguments in Bayesian statistics, with a particular emphasis on the search for mutually sufficient pairs of parameters and statistics.

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Nonparametric Bayesian Survival Analysisill proposal of robust predictive distributions is also discussed. In the simple model with censored observations and without explanatory variables or heterogeneity factors, a complete description of the posterior distribution of the “predictive” hazard function is provided in the conditional model and in the joint model.

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