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 Рейтинг: Цена: 93160.00 T Наличие на складе: Заказано в издательстве. 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.
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: McElreath, Richard Название: Statistical Rethinking ISBN: 036713991X ISBN-13(EAN): 9780367139919 Издательство: Taylor&Francis Рейтинг: Цена: 83690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Kedem Benjamin Et Al Название: Statistical Data Fusion ISBN: 9813200189 ISBN-13(EAN): 9789813200180 Издательство: World Scientific Publishing Рейтинг: Цена: 85530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 'The book provides a comprehensive review of the DRM approach to data fusion. It is well written and easy to follow, although the technical details are not trivial. The authors did an excellent job in making a concise introduction of the statistical techniques in data fusion. The book contains several real data ... Overall, I found that the book covers an important topic and the DRM is a promising tool in this area. Researchers on data fusion will surely find this book very helpful and I will use this book in studying with my PhD students.'Journal of the American Statistical AssociationThis book comes up with estimates or decisions based on multiple data sources as opposed to more narrowly defined estimates or decisions based on single data sources. And as the world is awash with data obtained from numerous and varied processes, there is a need for appropriate statistical methods which in general produce improved inference by multiple data sources.The book contains numerous examples useful to practitioners from genomics. Topics range from sensors (radars), to small area estimation of body mass, to the estimation of small tail probabilities, to predictive distributions in time series analysis.
Автор: Fred J. Hickernell, Peter Kritzer Название: Multivariate Algorithms and Information-Based Complexity ISBN: 3110633116 ISBN-13(EAN): 9783110633115 Издательство: Walter de Gruyter Цена: 128870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The series is devoted to the publication of high-level monographs, surveys and proceedings which cover the whole spectrum of computational and applied mathematics.
The books of this series are addressed to both specialists and advanced students.
Interested authors may submit book proposals to the Managing Editor or to any member of the Editorial Board.
Managing Editor Ulrich Langer, RICAM, Linz, Austria; Johannes Kepler University Linz, Austria
Автор: Kimmo Vehkalahti , Brian S. Everitt Название: Multivariate Analysis for the Behavioral Sciences, Second Edition ISBN: 0815385153 ISBN-13(EAN): 9780815385158 Издательство: Taylor&Francis Рейтинг: Цена: 86760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists.
Автор: Darwiche Название: Modeling and Reasoning with Bayesian Networks ISBN: 1107678420 ISBN-13(EAN): 9781107678422 Издательство: Cambridge Academ Рейтинг: Цена: 65470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis.
Автор: Ruey S. Tsay Название: Multivariate Time Series Analysis: With R and Financial Applications ISBN: 1118617908 ISBN-13(EAN): 9781118617908 Издательство: Wiley Рейтинг: Цена: 125610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.
Автор: Hougaard Philip Название: Analysis of Multivariate Survival Data ISBN: 1461270871 ISBN-13(EAN): 9781461270874 Издательство: Springer Рейтинг: Цена: 49370.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. As the field is rather new, the concepts and the possible types of data are described in detail.
Автор: Scott David W. Название: Multivariate Density Estimation ISBN: 0471697559 ISBN-13(EAN): 9780471697558 Издательство: Wiley Рейтинг: Цена: 101320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Written to convey an intuitive feeling for both theory and practice, this book illustrates what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and quadrivariate information.
Автор: Harlow Название: What If There Were No Significance Tests? ISBN: 1138892475 ISBN-13(EAN): 9781138892477 Издательство: Taylor&Francis Рейтинг: Цена: 67360.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.
Автор: Wickens Название: The Geometry of Multivariate Statistics ISBN: 1138882828 ISBN-13(EAN): 9781138882829 Издательство: Taylor&Francis Рейтинг: Цена: 58170.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.
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