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Titlebook: Case Studies in Applied Bayesian Data Science; CIRM Jean-Morlet Cha Kerrie L. Mengersen,Pierre Pudlo,Christian P. Robe Book 2020 The Editor

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书目名称Case Studies in Applied Bayesian Data Science
副标题CIRM Jean-Morlet Cha
编辑Kerrie L. Mengersen,Pierre Pudlo,Christian P. Robe
视频video
概述Presents a survey of state of the art aspects of applied Bayesian data science.Presents real-world case studies in applied Bayesian data science in the fields of health and ecology.Introduces new meth
丛书名称Lecture Notes in Mathematics
图书封面Titlebook: Case Studies in Applied Bayesian Data Science; CIRM Jean-Morlet Cha Kerrie L. Mengersen,Pierre Pudlo,Christian P. Robe Book 2020 The Editor
描述.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
出版日期Book 2020
关键词Applied Data Science; Applied Statistics; Bayesian Statistics; Case Studies in Data Science; Bayesian ne
版次1
doihttps://doi.org/10.1007/978-3-030-42553-1
isbn_softcover978-3-030-42552-4
isbn_ebook978-3-030-42553-1Series ISSN 0075-8434 Series E-ISSN 1617-9692
issn_series 0075-8434
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Theoretical aspects of phase-change alloys,frequentist scheme, meaning they are unable to reason about uncertainty in their predictions. This article introduces Bayesian Neural Networks (BNNs) and the seminal research regarding their implementation. Different approximate inference methods are compared, and used to highlight where future research can improve on current methods.
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CASE STUDIES: LEGACY CODE REUSE, this chapter, in the context of a substantive case study that aimed to tease out factors affecting the age at onset of the neurodegenerative medical condition, Parkinsons Disease (PD), with a particular focus on the role of a particular potential risk factor, pesticide exposure.
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A Survey of Bayesian Statistical Approaches for Big Dataent a survey of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data.
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An Ensemble Approach to Modelling the Combined Effect of Risk Factors on Age at Parkinson’s Disease this chapter, in the context of a substantive case study that aimed to tease out factors affecting the age at onset of the neurodegenerative medical condition, Parkinsons Disease (PD), with a particular focus on the role of a particular potential risk factor, pesticide exposure.
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