Statistics in matlab, Cho, Moonjung Martinez, Wendy L.
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: 9782.00 р. 13974.00-30% Наличие на складе: Есть (2 шт.) 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: 10480.00 р. 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: Christopher M. Bishop Название: Pattern Recognition and Machine Learning ISBN: 1493938436 ISBN-13(EAN): 9781493938438 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Автор: James, Gareth Witten, Daniela Hastie, Trevor Tibsh Название: Introduction to statistical learning ISBN: 1071614177 ISBN-13(EAN): 9781071614174 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more.
Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers.
An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.
Автор: Bradley Efron , Trevor Hastie Название: Computer Age Statistical Inference, Student Edition ISBN: 1108823416 ISBN-13(EAN): 9781108823418 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Field, Andy Miles, Jeremy Field, Zoe Название: Discovering statistics using r ISBN: 1446289133 ISBN-13(EAN): 9781446289136 Издательство: Sage Publications Рейтинг: Цена: 9504.00 р. Наличие на складе: Поставка под заказ.
Описание: The R version of Andy Field`s hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.
This book takes recent theoretical advances in Finance and Economics and shows how they can be implemented in the real world. It presents tactics for using mathematical and simulation models to solve complex tasks of forecasting income, valuing businesses, predicting retail sales, and evaluating markets and tax and regulatory problems.
Business Economics and Finance with Matlab, GIS, and Simulation Models provides a unique overview of sophisticated business and financial applications. It describes models that have been developed for analysis of retail sales, tax policy, location, economic impact, public policy issues, and other challenges faced by executives, investors, and economists on a daily basis. It also offers groundbreaking insight into the many calculation and modeling tools that can be remotely hosted and run over the Internet, resulting in substantial user benefits and cost savings.
This book is the first to fully explore the capabilities of MATLAB in the field of business economics, and explain how the benefits of sophisticated mathematical models can be provided to users via the Internet, using a thin-client environment. Many techniques directly incorporate geographic information and GIS in a way that was impossible until quite recently. Some techniques, such as fuzzy logic, retail sales, economic and fiscal impact models, and other Matlab and Simulink models, are described for the first time in print in this book. The sections on business income and value break new ground by directly incorporating uncertainty, real option value, and prediction of variables using Ito and jump processes. Using dozens of examples, hundreds of references, and rigorous explanations of both theory and practice, it will become a prized reference for analysts demanding the best techniques.
Автор: Mustafy, Tanvir ; Rahman, Tauhid ; Siddiqui, Nafis Название: Engineering Data Analysis with Matlab(r) ISBN: 1032507713 ISBN-13(EAN): 9781032507712 Издательство: Taylor&Francis Рейтинг: Цена: 11023.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Martinez, Wendy L. Martinez, Angel R. Название: Computational statistics handbook with matlab ISBN: 1032179589 ISBN-13(EAN): 9781032179582 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This third edition covers today`s most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. This edition uses the latest version of MATLAB (R) and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new
Автор: Field, Andy Название: Discovering Statistics Using R ISBN: 1446200469 ISBN-13(EAN): 9781446200469 Издательство: Sage Publications Рейтинг: Цена: 12830.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The R version of Andy Field`s hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.
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