Overview
- It reports the best work of young Bayesian statisticians
- It provides a quite large overview of the current research in the field
- It can be seen as a springboard for talented young Bayesian to write their first international paper
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 405)
Included in the following conference series:
Conference proceedings info: BAYSM 2021.
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Table of contents (11 papers)
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Front Matter
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Back Matter
Other volumes
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New Frontiers in Bayesian Statistics
Keywords
About this book
This book presents a selection of peer-reviewed contributions to the fifth Bayesian Young Statisticians Meeting, BaYSM 2021, held virtually due to the COVID-19 pandemic on 1-3 September 2021. Despite all the challenges of an online conference, the meeting provided a valuable opportunity for early career researchers, including MSc students, PhD students, and postdocs to connect with the broader Bayesian community.
The proceedings highlight many different topics in Bayesian statistics, presenting promising methodological approaches to address important challenges in a variety of applications. The book is intended for a broad audience of people interested in statistics, and provides a series of stimulating contributions on theoretical, methodological, and computational aspects of Bayesian statistics.
Editors and Affiliations
About the editors
Federico Camerlenghi is an Assistant Professor of Statistics at the Department of Economics, Management and Statistics and a board member of the Ph.D. in Economics, Statistics and Data Science at the University of Milano-Bicocca, Italy. His research mainly focuses on the construction and investigation of Bayesian nonparameteric models to handle exchangeable and partially exchangeable data. He received the Savage award in Theory & Methods in 2017, and he was the chair of the junior Section of the International Society for Bayesian Analysis (j-ISBA) in 2019.
Sally Paganin is a Research fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health, and treasurer of the junior Section of the International Society for Bayesian Analysis (j-ISBA). Previously, she was a Postdoctoral Researcher at UC Berkeley, and a core team member of the NIMBLE software project. Her research focuses on Bayesian methods and statistical models for complex data, along with the development of statistical software and algorithms.
Bibliographic Information
Book Title: New Frontiers in Bayesian Statistics
Book Subtitle: BAYSM 2021, Online, September 1–3
Editors: Raffaele Argiento, Federico Camerlenghi, Sally Paganin
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-031-16427-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-16426-2Published: 27 November 2022
Softcover ISBN: 978-3-031-16429-3Published: 27 November 2023
eBook ISBN: 978-3-031-16427-9Published: 26 November 2022
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XI, 117
Number of Illustrations: 7 b/w illustrations, 14 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Statistical Theory and Methods, Statistics and Computing/Statistics Programs