Avalos Pacheco, A., De Vito, R., & Maire, F. (Eds.). (2023). Bayesian Statistics, New Generations New Approaches : BAYSM 2022, Montréal, Canada, June 22–23 (Vol. 435). Springer. https://doi.org/10.1007/978-3-031-42413-7
Avalos Pacheco, Alejandra De Vito, Roberta Maire, Florian
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Organisational Unit:
E105-08 - Forschungsbereich Angewandte Statistik
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Series:
Springer Proceedings in Mathematics & Statistics
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ISBN:
978-3-031-42412-0 978-3-031-42413-7
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Volume:
435
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Date (published):
2023
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Publisher:
Springer
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Keywords:
Bayesian non parametric; BAYSM; Bayesian data analysis; Bayesian modeling; Bayesian dimension reduction techniques; Bayesian dimension reduction techniques; Bayesian computation; Bayesian Cluster methods; Bayesian process
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Abstract:
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.
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Research Areas:
Mathematical and Algorithmic Foundations: 30% Computer Science Foundations: 50% Modeling and Simulation: 20%
