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Bayesian Statistics, New Generations New Approaches: BAYSM 2022, Montréal, Canada, June 22–23 /

Bayesian Statistics, New Generations New Approaches: BAYSM 2022, Montréal, Canada, June 22–23 /
Kataloginformation
Feldname Details
Dewey Class 519.5
Titel Bayesian Statistics, New Generations New Approaches (EBook :) : BAYSM 2022, Montréal, Canada, June 22–23 / / edited by Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire.
Added Personal Name Avalos-Pacheco, Alejandra
De Vito, Roberta
Maire, Florian
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2023.
Veröffentl Cham : : Springer International Publishing : : Imprint: Springer, , 2023.
Physical Details VIII, 115 p. 34 illus., 22 illus. in color. : online resource.
Reihe Springer Proceedings in Mathematics & Statistics 2194-1017 ; ; 435
ISBN 9783031424137
Summary Note 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.:
Contents note 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.
Mode of acces to digital resource Digital reproduction.-
Cham :
Springer International Publishing,
2023. -
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site https://doi.org/10.1007/978-3-031-42413-7
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  • Schlagwörter: .
  • Bayesian Inference .
  • Bayesian Network .
  • Statistical Theory and Methods .
  • Statistics .

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    Kataloginformation53928 Datensatzanfang . Kataloginformation53928 Seitenanfang .
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