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Bayesian statistics, new generations new approaches = BAYSM 2022, Montreal, Canada, June 22-23 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Bayesian statistics, new generations new approaches/ edited by Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire.
其他題名:	BAYSM 2022, Montreal, Canada, June 22-23 /
其他題名:	BAYSM 2022
其他作者:	Maire, Florian.
團體作者:	Workshop on the Preservation of Stability under Discretization
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	viii, 115 p. :illustrations (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Bayesian Inference. -
電子資源:	https://doi.org/10.1007/978-3-031-42413-7
ISBN:	9783031424137

Bayesian statistics, new generations new approaches = BAYSM 2022, Montreal, Canada, June 22-23 /
Bayesian statistics, new generations new approachesBAYSM 2022, Montreal, Canada, June 22-23 /[electronic resource] :BAYSM 2022edited by Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire. - Cham :Springer International Publishing :2023. - viii, 115 p. :illustrations (some col.), digital ;24 cm. - Springer proceedings in mathematics & statistics,v. 4352194-1017 ;. - Springer proceedings in mathematics & statistics ;v.24..

J. Owen, I. Vernon, J. Carter, Bayesian Emulation of Complex Computer Models with Structured Partial Discontinuities -- B. Hansen, A. Avalos-Pacheco, M. Russo, Roberta De Vito, A Variational Bayes Approach to Factor Analysis. P. Strong, Jim Q. Smith, Scalable Model Selection for Staged Trees: Mean-posterior Clustering and Binary Trees -- G. Vasdekis, Gareth O. Roberts, Speeding up the Zig-Zag process -- V. Ghidini, S. Legramanti, R. Argiento, Extended Stochastic Block Model with Spatial Covariates for Weighted Brain Networks -- A. Lachi, C. Viscardi, M. Baccini, Approximate Bayesian inference for smoking habit dynamics in Tuscany.

This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22-23, 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.

ISBN: 9783031424137

Standard No.: 10.1007/978-3-031-42413-7doiSubjects--Topical Terms:

1211345
Bayesian Inference.

LC Class. No.: QA279.5 / .B39 2022

Dewey Class. No.: 519.542

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