| 书目名称 | New Frontiers in Bayesian Statistics | | 副标题 | BAYSM 2021, Online, | | 编辑 | Raffaele Argiento,Federico Camerlenghi,Sally Pagan | | 视频video | | | 概述 | 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 th | | 丛书名称 | Springer Proceedings in Mathematics & Statistics | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Conference proceedings 2022 | | 关键词 | Bayesian Statistics; Mixture models; Markov Chain; Monte Carlo algorithms; Bayesian Nonparametrics; Survi | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-16427-9 | | isbn_softcover | 978-3-031-16429-3 | | isbn_ebook | 978-3-031-16427-9Series ISSN 2194-1009 Series E-ISSN 2194-1017 | | issn_series | 2194-1009 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 19:36:19
