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Mathematical Theory of Bayesian Statistics, Watanabe Sumio


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Автор: Watanabe Sumio
Название:  Mathematical Theory of Bayesian Statistics
ISBN: 9780367734817
Издательство: Taylor&Francis
Классификация:


ISBN-10: 0367734818
Обложка/Формат: Paperback
Страницы: 332
Вес: 0.38 кг.
Дата издания: 18.12.2020
Язык: English
Размер: 23.11 x 15.49 x 2.03 cm
Читательская аудитория: Tertiary education (us: college)
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior distribution cannot be approximated by any normal distribution.





Features









  • Explains Bayesian inference not subjectively but objectively.






  • Provides a mathematical framework for conventional Bayesian theorems.






  • Introduces and proves new theorems.






  • Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view.






  • Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests.






This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians.





Author



Sumio Watanabe is a professor of Department of Mathematical and Computing Science at Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics.






Epidemiology:  Key to Public Health. 2 ed.

Автор: Krickeberg Klaus, Van Trong Pham, Thi My Hanh Pham
Название: Epidemiology: Key to Public Health. 2 ed.
ISBN: 3030163679 ISBN-13(EAN): 9783030163679
Издательство: Springer
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Цена: 13974.00 р.
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Описание: ?This unique textbook presents the field of modern epidemiology as a whole; it does not restrict itself to particular aspects. It stresses the fundamental ideas and their role in any situation of epidemiologic practice. Its structure is largely determined by didactic viewpoints.Epidemiology is the art of defining and investigating the influence of factors on the health of populations. Hence the book starts by sketching the role of epidemiology in public health. It then treats the epidemiology of many particular diseases; mathematical modelling of epidemics and immunity; health information systems; statistical methods and sample surveys; clinical epidemiology including clinical trials; nutritional, environmental, social, and genetic epidemiology; and the habitual tools of epidemiologic studies. The book also reexamines the basic difference between the epidemiology of infectious diseases and that of non-infectious ones.The organization of the topics by didactic aspects makes the book ideal for teaching. All examples and case studies are situated in a single country, namely Vietnam; this provides a particularly vivid picture of the role of epidemiology in shaping the health of a population. It can easily be adapted to other developing or transitioning countries.This volume is well suited for courses on epidemiology and public health at the upper undergraduate and graduate levels, while its specific examples make it appropriate for those who teach these fields in developing or emerging countries. New to this edition, in addition to minor revisions of almost all chapters:• Updated data about infectious and non-infectious diseases• An expanded discussion of genetic epidemiology• A new chapter, based on recent research of the authors, on how to build a coherent system of Public Health by using the insights provided by this volume.

The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 11528.00 р.
Наличие на складе: Заказано в издательстве.

Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Data-driven science and engineering

Автор: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 7918.00 р.
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Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

Computer Age Statistical Inference, Student Edition

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 5069.00 р.
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Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Statistical Rethinking

Автор: McElreath, Richard
Название: Statistical Rethinking
ISBN: 036713991X ISBN-13(EAN): 9780367139919
Издательство: Taylor&Francis
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Цена: 12554.00 р.
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Описание: Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.

Mathematical statistics with applications

Автор: Wackerly, Dennis Mendenhall, William Scheaffer, Ri
Название: Mathematical statistics with applications
ISBN: 0495385069 ISBN-13(EAN): 9780495385066
Издательство: Cengage Learning
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Цена: 9344.00 р.
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Описание: Prepare for exams and succeed in your mathematics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in MATHEMATICAL STATISTICS WITH APPLICATIONS, 7th Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.

A Course in Mathematical and Statistical Ecology

Автор: Anil Gore; S.A. Paranjpe
Название: A Course in Mathematical and Statistical Ecology
ISBN: 9048156165 ISBN-13(EAN): 9789048156160
Издательство: Springer
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Цена: 12577.00 р.
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Описание: A Course in Mathematical and Statistical Ecology

Portfolio theory and arbitrage

Автор: Karatzas, Ioannis Kardaras, Constantinos
Название: Portfolio theory and arbitrage
ISBN: 1470465981 ISBN-13(EAN): 9781470465988
Издательство: Mare Nostrum (Eurospan)
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Цена: 10659.00 р.
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Описание: This book develops a mathematical theory for finance, based on a simple and intuitive absence-of-arbitrage principle. This posits that it should not be possible to fund a non-trivial liability, starting with initial capital arbitrarily near zero. The principle is easy-to-test in specific models, as it is described in terms of the underlying market characteristics; it is shown to be equivalent to the existence of the so-called ""Kelly"" or growth-optimal portfolio, of the log-optimal portfolio, and of appropriate local martingale deflators. The resulting theory is powerful enough to treat in great generality the fundamental questions of hedging, valuation, and portfolio optimization.The book contains a considerable amount of new research and results, as well as a significant number of exercises. It can be used as a basic text for graduate courses in Probability and Stochastic Analysis, and in Mathematical Finance. No prior familiarity with finance is required, but it is assumed that readers have a good working knowledge of real analysis, measure theory, and of basic probability theory. Familiarity with stochastic analysis is also assumed, as is integration with respect to continuous semimartingales.

Practical Smoothing: The Joys of P-splines

Автор: Paul H.C. Eilers, Brian D. Marx
Название: Practical Smoothing: The Joys of P-splines
ISBN: 1108482953 ISBN-13(EAN): 9781108482950
Издательство: Cambridge Academ
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Цена: 8554.00 р.
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Описание: P-splines are widely used in statistics and machine learning for smoothing out noise in data and to avoid overtraining. This practical guide covers theory and a range of standard and non-standard applications with code in R for professionals and researchers looking for a simple, flexible and powerful smoothing tool.

Measuring and Reasoning

Автор: Bookstein, Fred L.,
Название: Measuring and Reasoning
ISBN: 1107024153 ISBN-13(EAN): 9781107024151
Издательство: Cambridge Academ
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Цена: 7760.00 р.
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Описание: This exploration of empirical inference in science ranges over topics as diverse as the mass extinction of the dinosaurs, Peirce`s concept of abduction, multiple regression, and the analysis of patterns in astrophysics. At its heart is a formal description of the process by which scientific measurements support convincing explanations of the world around us.

Dynamic Documents with R and knitr, Second Edition

Автор: Xie Y.
Название: Dynamic Documents with R and knitr, Second Edition
ISBN: 1498716962 ISBN-13(EAN): 9781498716963
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание:

Quickly and Easily Write Dynamic Documents

Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web pages to virtually any documents related to statistical graphics, computing, and data analysis. The book covers basic applications for beginners while guiding power users in understanding the extensibility of the knitr package.

New to the Second Edition

  • A new chapter that introduces R Markdown v2
  • Changes that reflect improvements in the knitr package
  • New sections on generating tables, defining custom printing methods for objects in code chunks, the C/Fortran engines, the Stan engine, running engines in a persistent session, and starting a local server to serve dynamic documents

Boost Your Productivity in Statistical Report Writing and Make Your Scientific Computing with R Reproducible

Like its highly praised predecessor, this edition shows you how to improve your efficiency in writing reports. The book takes you from program output to publication-quality reports, helping you fine-tune every aspect of your report.

Spectral Analysis for Univariate Time Series

Автор: Donald B. Percival, Andrew T. Walden
Название: Spectral Analysis for Univariate Time Series
ISBN: 1107028140 ISBN-13(EAN): 9781107028142
Издательство: Cambridge Academ
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Цена: 14573.00 р.
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Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.


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