Bayesian statistics, new generations new approaches : BAYSM 2022, Montréal, Canada, June 22-23 / Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire, editors.

This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montral, Canada, held on June 2223, titled "Bayesian Statistics, New Generations New Approaches". This collection features selected peer-reviewed contributions that showcase the vibrant and divers...

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Bibliographic Details
Corporate Author: BAYSM Montréal, Québec
Other Authors: Avalos-Pacheco, Alejandra (Editor), De Vito, Roberta (Editor), Maire, Florian (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2023]
Series:Springer proceedings in mathematics & statistics ; v. 435.
Subjects:
Online Access:Click for online access

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245 1 0 |a Bayesian statistics, new generations new approaches :  |b BAYSM 2022, Montréal, Canada, June 22-23 /  |c Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire, editors. 
246 3 |a BAYSM 2022 
264 1 |a Cham, Switzerland :  |b Springer,  |c [2023] 
300 |a 1 online resource (viii, 115 pages) :  |b illustrations (some color). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Springer proceedings in mathematics & statistics series ;  |v volume 435 
504 |a Includes bibliographical references. 
505 8 |a Intro -- Preface -- Contents -- Bayesian Emulation of Complex Computer Models with Structured Partial Discontinuities -- 1 Introduction -- 2 Bayesian Emulation with Partial Discontinuities -- 2.1 Emulation of Computer Models -- 2.2 Torn Embeddings in Higher Dimensions -- 2.3 Controlling for the Induced Local Warping Effect -- 2.4 Controlling for the Global Impact of the Embedding Using Non-stationary Emulation -- 3 Application: TNO OLYMPUS Well Placement Optimisation Challenge -- 4 Conclusion -- References -- A Variational Bayes Approach to Factor Analysis -- 1 Background -- 2 Methods 
505 8 |a 3 Results -- 4 Conclusions -- References -- Scalable Model Selection for Staged Trees: Mean-posterior Clustering and Binary Trees -- 1 Introduction -- 2 Preliminaries -- 2.1 Staged Trees -- 2.2 Conjugate Learning and Model Selection -- 3 Methods -- 3.1 Totally Ordered Hyperstage -- 4 Mean Posterior Probabilities -- 4.1 Resize Operator -- 5 A Comparative Analysis of Competing Methodologies -- 6 Christchurch Health and Development Study Example -- 7 Discussion -- References -- Speeding up the Zig-Zag Process -- 1 Introduction -- 2 The SUZZ Process -- 3 Theoretical Results -- 4 Numerical Examples 
505 8 |a Mixing Times of a Gibbs Sampler for Probit Hierarchical Models -- 1 Introduction -- 2 Probit Hierarchical Models -- 3 Theoretical Results on Mixing Times -- 4 Numerical Illustration -- 5 Conclusions -- References -- A Note on the Dependence Structure of Hierarchical Completely Random Measures -- 1 Introduction -- 2 Hierarchical Completely Random Measures -- 3 Dependence Structure -- 4 Discussion -- 5 Proofs -- References -- Observed Patterns of Heat Wave Intensities with Respect to Time and Global Surface Temperature -- 1 Introduction -- 2 Methods -- 3 Applications 
505 8 |a 3.1 Heat Wave Maximum Intensity Over Time -- 3.2 Heat Wave Maximum Intensity and Global Surface Temperature -- 4 Conclusions -- References -- Expectation Propagation for the Smoothing Distribution in Dynamic Probit -- 1 Introduction -- 2 Literature Review -- 3 Expectation Propagation (EP) for the Dynamic Probit -- 3.1 Implementation Without p n times p npntimespn Matrix Inversions -- 3.2 Implementation Without p n times p npntimespn Matrix Updates -- 3.3 Computational Costs -- 4 Financial Illustration -- 5 Discussion -- References 
520 |a This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montral, Canada, held on June 2223, titled "Bayesian Statistics, New Generations New Approaches". This collection features selected peer-reviewed contributions that showcase the vibrant and diverse research presented at meeting. This book is intended for a broad audience interested in statistics and aims at providing stimulating contributions to theoretical, methodological, and computational aspects of Bayesian statistics. The contributions highlight various topics in Bayesian statistics, presenting promising methodological approaches to address critical challenges across diverse applications. This compilation stands as a testament to the talent and potential within the j-ISBA community. This book is meant to serve as a catalyst for continued advancements in Bayesian methodology and its applications and encourages fruitful collaborations that push the boundaries of statistical research. 
588 |a Description based on online resource; title from digital title page (viewed on January 23, 2024). 
650 0 |a Bayesian statistical decision theory  |v Congresses. 
650 7 |a Bayesian statistical decision theory.  |2 fast  |0 (OCoLC)fst00829019 
655 7 |a proceedings (reports)  |2 aat 
655 7 |a Conference papers and proceedings.  |2 fast  |0 (OCoLC)fst01423772 
655 7 |a Conference papers and proceedings.  |2 lcgft 
655 7 |a Actes de congrès.  |2 rvmgf 
700 1 |a Avalos-Pacheco, Alejandra,  |e editor. 
700 1 |a De Vito, Roberta,  |e editor. 
700 1 |a Maire, Florian,  |e editor. 
776 0 8 |i Print version:  |a Avalos-Pacheco, Alejandra  |t Bayesian Statistics, New Generations New Approaches  |d Cham : Springer International Publishing AG,c2024  |z 9783031424120 
830 0 |a Springer proceedings in mathematics & statistics ;  |v v. 435. 
856 4 0 |u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-031-42413-7  |y Click for online access 
903 |a SPRING-ALL2023 
994 |a 92  |b HCD