03189nam a22004215i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072002300183072001500206245014800221250001800369264006900387300004500456336002600501337002600527338003600553347002400589505093800613520076001551650001802311650001602329650002402345650002202369700008302391700007902474710003402553773002602587776003602613776003602649776003602685856004602721978-3-031-61329-6DE-He21320251030113238.0cr nn 008mamaa241022s2024    sz |    s    |||| 0|eng d  a97830316132967 a10.1007/978-3-031-61329-62doi 4aQA276-280 7aPBT2bicssc 7aMAT0290002bisacsh 7aPBT2thema10aNonparametric Bayesian Inferenceh[electronic resource] :bContributions by Jean-Marie Rolin /cedited by Jean-Pierre Florens, Michel Mouchart.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXIII, 376 p. 17 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aChapter 1. On the a-Algebraic Realization Problem -- Chapter 2. Weak Conditional Independence And Relative Invariance in Bayesian Statistics -- Chapter 3. Some Useful Properties of the Dirichlet Process -- Chapter 4. On the Distribution of Jumps of the Dirichlet Process -- Chapter 5. Bayes, Bootstrap, Moments -- Chapter 6. Smooth vs. likelihood estimation for a class of mixtures of discrete distributions -- Chapter 7. Bayesian Encompassing Specification Tests of a Parametric Model against a Non Parametric Alternative -- Chapter 8. Nonparametric Bayesian Survival Analysis -- Chapter 9. Simulation of Posterior Distributions in Nonparametric Censored Analysis -- Chapter 10. Bayesian Identification of Semi-Parametric Binary Response Models -- Chapter 11. Survival Data with Explanatory Processes: A Full Nonparametric Bayesian Analysis -- Chapter 12. Nonparametric Competing Risks Models: Identification and Strong Consistency.  aThis book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain and died on November 5th, 2018. He made important contributions in mathematical statistics with applications to different fields like econometrics or biometrics.These papers cover a variety of topics, including: • The Mathematical structure of the Bayesian model and the main concepts (sufficiency, ancillarity, invariance…) • Representation of the Dirichlet processes and of the associated Polya urn model and applications to nonparametric bayesian analysis. • Contributions to duration models and to their non parametric bayesian treatment. 0aStatistics .14aStatistics.24aBayesian Inference.24aBayesian Network.1 aFlorens, Jean-Pierre.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aMouchart, Michel.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303161328908iPrinted edition:z978303161330208iPrinted edition:z978303161331940uhttps://doi.org/10.1007/978-3-031-61329-6