Overview
- Plenary lecturers and senior discussants of BAYSM 2013 provide a discussion of recent developments in Bayesian statistics
- Highlights contributions of young researchers to BAYSM 2013 through comprehensive research papers
- Includes suggested research topics and predictions for the future of Bayesian statistics
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 63)
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Table of contents (39 papers)
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Front Matter
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Theoretical Bayes
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Front Matter
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Computational Bayes
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Front Matter
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Keywords
About this book
The first Bayesian Young Statisticians Meeting, BAYSM 2013, has provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and post-docs dealing with Bayesian statistics to connect with the Bayesian community at large, exchange ideas, and network with scholars working in their field. The Workshop, which took place June 5th and 6th 2013 at CNR-IMATI, Milan, has promoted further research in all the fields where Bayesian statistics may be employed under the guidance of renowned plenary lecturers and senior discussants. A selection of the contributions to the meeting and the summary of one of the plenary lectures compose this volume.
Editors and Affiliations
About the editors
Ettore Lanzarone is a Permanent Researcher at the division of Milan of the Institute of Applied Mathematics and Information Technology (IMATI) of the National Research Council of Italy (CNR), Milan, Italy. He is also Adjunct Professor Mathematical Analysis at the Politecnico di Milano, Milan, Italy. He obtained his Ph.D. in Bioengineering in June 2008 at the Politecnico di Milano, and his master degree in Biomedical Engineering cum laude in April 2004 at the Politecnico di Milano. He is member of the European Working Group on Operational Research Applied to Health Services (ORAHS) and of the Italian National Bioengineering Group (GNB). Â His current research interests include: parameter estimation and stochastic evolution of dynamic systems described by ordinary and partial differential equations; stochastic models for estimating the demand and planning the activities in healthcare structures; modelling and in-vitro studies of the cardiovascular fluid dynamics.
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Francesca Ieva is a Postdoctoral Research Fellow at the Modeling and Scientific Computing Lab (MOX), Department of Mathematics, Politecnico di Milano, Milan, Italy. She obtained her Ph.D. in Mathematical Models and Methods for Engineering and her master degree in Mathematical Engineering at the Politecnico di Milano in 2012 and 2008, respectively. She is member of ISBA (and Program Chair of the junior section), RSS, SIS (and Chair of the young section) and SIAM. Her research activities include Statistical Learning in Biomedical context, focused on modelling data arising from integration of clinical surveys and administrative databanks, Clinical Biostatistics, Healthcare assessment, Mixed Effects Models and Semi-parametric Bayesian hierarchical models, Depth Measures and Multivariate Functional Data Analysis for applications to ECG signals, Multi State Models for the analysis of chronic diseases progression like heart failures.
Bibliographic Information
Book Title: The Contribution of Young Researchers to Bayesian Statistics
Book Subtitle: Proceedings of BAYSM2013
Editors: Ettore Lanzarone, Francesca Ieva
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-319-02084-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-02083-9Published: 10 December 2013
Softcover ISBN: 978-3-319-34307-5Published: 23 August 2016
eBook ISBN: 978-3-319-02084-6Published: 22 November 2013
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: X, 214
Number of Illustrations: 10 b/w illustrations, 21 illustrations in colour
Topics: Statistical Theory and Methods, Statistics, general, Statistics for Social Sciences, Humanities, Law