Nonparametric Bayesian Inference

Edited by Jean-Pierre Florens () and Michel Mouchart ()

in Springer Books from Springer

Date: 2024
ISBN: 978-3-031-61329-6
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Chapters in this book:

Ch Chapter 1 On the σ-Algebraic Realization Problem

Michel Mouchart and Jean-Marie Rolin

Ch Chapter 10 Nonparametric Competing Risks Models: Identification and Strong Consistency

Jean-Marie Rolin

Ch Chapter 11 Survival Data with Explanatory Processes: A Full Nonparametric Bayesian Analysis

Jean-Marie Rolin

Ch Chapter 12 Duration Model Bayesian Semi-parametric Approach

Michel Mouchart, Jean-Marie Rolin and Joseph Hakizamungu

Ch Chapter 13 Smooth Versus Likelihood Estimation for a Class of Mixtures of Discrete Distributions

Valentin Patilea and Jean-Marie Rolin

Ch Chapter 14 Identification of Semiparametric Binary Response Models: Sampling Theory and Bayesian Approaches Compared

Michel Mouchart, Jean-Marie Rolin and Eliana Scheihing

Ch Chapter 2 Weak Conditional Independence and Relative Invariance in Bayesian Statistics

Jean-Pierre Florens, Michel Mouchart and Jean-Marie Rolin

Ch Chapter 3 Some Useful Properties of the Dirichlet Process

Jean-Marie Rolin

Ch Chapter 4 On the Distribution of Jumps of the Dirichlet Process

Jean-Marie Rolin

Ch Chapter 5 Bayes, Bootstrap, and Moments

Jean-Pierre Florens and Jean-Marie Rolin

Ch Chapter 6 On the Dirichlet Random Measure: Alternative Approach

Jean-Marie Rolin and Joseph Hakizamungu

Ch Chapter 7 Bayesian Encompassing Specification Tests of a Parametric Model Against a Nonparametric Alternative

Jean-Pierre Florens, Jean-Francois Richard and Jean-Marie Rolin

Ch Chapter 8 Nonparametric Bayesian Survival Analysis

Jean-Marie Rolin

Ch Chapter 9 Simulation of Posterior Distributions in Nonparametric Censored Analysis

Jean-Pierre Florens and Jean-Marie Rolin

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DOI: 10.1007/978-3-031-61329-6

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