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Titlebook: Directional Statistics for Innovative Applications; A Bicentennial Tribu Ashis SenGupta,Barry C. Arnold Book 2022 The Editor(s) (if applica

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书目名称Directional Statistics for Innovative Applications
副标题A Bicentennial Tribu
编辑Ashis SenGupta,Barry C. Arnold
视频video
概述Presents recent phenomenal development in theory and emerging methods for applications in directional statistics.Pays a statistical tribute to Florence Nightingale—the lady who gave us the “rose diagr
丛书名称Forum for Interdisciplinary Mathematics
图书封面Titlebook: Directional Statistics for Innovative Applications; A Bicentennial Tribu Ashis SenGupta,Barry C. Arnold Book 2022 The Editor(s) (if applica
描述In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on..
出版日期Book 2022
关键词Directional Statistics; Multivariate Analysis; Regression Analysis; Big Data Analytics; Statistical Mach
版次1
doihttps://doi.org/10.1007/978-981-19-1044-9
isbn_softcover978-981-19-1046-3
isbn_ebook978-981-19-1044-9Series ISSN 2364-6748 Series E-ISSN 2364-6756
issn_series 2364-6748
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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2364-6748 nference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on..978-981-19-1046-3978-981-19-1044-9Series ISSN 2364-6748 Series E-ISSN 2364-6756
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Book 2022aximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on..
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Set-Membership Adaptive Filterings a point on a sphere. We fit mixtures of Kent distributions to different subsets of the hydrogen bond data to gain insight into how the secondary structure elements bond together, since the distribution of hydrogen bonds depends on which secondary structure elements are involved.
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