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Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018
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Catalogue Information
Field name
Details
Dewey Class
519.5
Title
Case Studies in Applied Bayesian Data Science : CIRM Jean-Morlet Chair, Fall 2018 (EB) / Kerrie L. Mengersen, Pierre Pudlo, Christian P. Robert, Editors
Author
Mengersen, Kerrie L.
Added Personal Name
Pudlo, Pierre
Robert, Christian P.
Other name(s)
CIRM
SpringerLink (Online service)
Publication
Cham, Switzerland AG : Springer Nature , 2020
Physical Details
vi, 420 pages
Series
Lecture Notes in Mathematics
; 2259
ISBN
978-3-030-42553-1
Summary Note
Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor.The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields.While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution.The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.:
Mode of acces to digital resource
Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
https://doi.org/10.1007/978-3-030-42553-1
Links to Related Works
Subject References:
Bayesian computation
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Bayesian Inference
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Big Data
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Markov random fields
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Probabilities
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Probability
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Statistics
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Authors:
Mengersen, Kerrie L.
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Pudlo, Pierre
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Robert, Christian P.
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Corporate Authors:
CIRM
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SpringerLink (Online service)
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Series:
Lecture Notes in Mathematics
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Classification:
519.5
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