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: James, Gareth Witten, Daniela Hastie, Trevor Tibsh Название: Introduction to statistical learning ISBN: 1071614177 ISBN-13(EAN): 9781071614174 Издательство: Springer Рейтинг: Цена: 55890.00 T 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: 33790.00 T 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: 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: Krijnen, Wim P. , Wit, Ernst C. Название: Computational and statistical methods for chemical engineering ISBN: 1032013249 ISBN-13(EAN): 9781032013244 Издательство: Taylor&Francis Рейтинг: Цена: 76550.00 T Наличие на складе: Нет в наличии. Описание: Before the data revolution, most books focused either on mathematical modeling of chemical processes or exploratory chemometrics. This book aims to combine these two approaches and provide aspiring chemical engineers a single, comprehensive account of computational and statistical methods. Each chapter is accompanied by extensive exercises.
Автор: Gelfand, Alan E. Fuentes, Montserrat Guttorp, Pete Название: Handbook of spatial statistics ISBN: 1420072870 ISBN-13(EAN): 9781420072877 Издательство: Taylor&Francis Рейтинг: Цена: 103610.00 T Наличие на складе: Есть Описание: Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
Автор: Grace Y. Yi, Aurore Delaigle, Paul Gustafson Название: Handbook of Measurement Error Models ISBN: 1138106402 ISBN-13(EAN): 9781138106406 Издательство: Taylor&Francis Рейтинг: Цена: 219470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reference text for statistical methods and applications for measurement error models for: researchers who work with error-contaminated data, graduate students from statistics and biostatistics, analysts in multiple fields, including medical research, biosciences, nutritional studies, epidemiological studies and environmental studies.
Автор: Christopher H Schmid Название: Handbook Of Meta-Analysis ISBN: 1498703984 ISBN-13(EAN): 9781498703987 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the years as the need for a robust evidence base has become clear in many scientific areas like medicine and health, social sciences, education, psychology, ecology and economics.
Автор: He, Yulei Название: Multiple Imputation Analysis For Ob ISBN: 1498722067 ISBN-13(EAN): 9781498722063 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.
Автор: Tuckwell, Henry C. Название: Elementary Applications of Probability Theory ISBN: 0367449056 ISBN-13(EAN): 9780367449056 Издательство: Taylor&Francis Рейтинг: Цена: 63280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences, engineering, and physical, social and statistical sciences. It also introduces the topic of stochastic differential equations and their applications.
Автор: Burr, John T. Название: Elementary Statistical Quality Control ISBN: 0367578123 ISBN-13(EAN): 9780367578121 Издательство: Taylor&Francis Рейтинг: Цена: 50010.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Wilks Samuel Stanley, Wilks S. S. Название: Elementary Statistical Analysis ISBN: 069162755X ISBN-13(EAN): 9780691627557 Издательство: Wiley Рейтинг: Цена: 50690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
A beginning text especially designed for those who probably will not go in to statistics professionally but who plan to go into the physical, biological, and social sciences. The material presupposes only one semester of elementary mathematical analysis.
Originally published in 1948. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
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