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New Frontiers in Bayesian Statistics : BAYSM 2021, Online, September 1-3 /

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 ca...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Argiento, Raffaele (Editor), Camerlenghi, Federico (Editor), Paganin, Sally (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2022.
Edition:1st ed. 2022.
Series:Springer Proceedings in Mathematics & Statistics, 405
Subjects:
Mathematical statistics.
Stochastic processes.
Stochastic models.
Stochastic analysis.
Markov processes.
Mathematical Statistics.
Stochastic Networks.
Stochastic Modelling.
Stochastic Analysis.
Markov Process.
Stochastic Processes.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary: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.
Physical Description:1 online resource (XI, 117 pages 21 illustrations, 14 illustrations in color)
ISBN:9783031164279
ISSN:2194-1017 ;
DOI:10.1007/978-3-031-16427-9