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An Introduction to Statistical Learning, James Gareth

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Цена: 5609р.
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Автор: James Gareth
Название:  An Introduction to Statistical Learning   (Джеймс Гарет: Введение в изучение статистики)
Издательство: Springer
Классификация:
Вероятность и статистика
Прикладная математика
Физика
Математическое и статистическое программное обеспечение

ISBN: 1461471370
ISBN-13(EAN): 9781461471370
ISBN: 1-461-47137-0
ISBN-13(EAN): 978-1-461-47137-0
Обложка/Формат: Hardback
Страницы: 426
Вес: 0.852 кг.
Дата издания: 25.06.2013
Серия: Springer texts in statistics
Язык: ENG
Иллюстрации: 4 black & white illustrations, 146 colour illustrations, 10 black & white tables, biography
Размер: 235 X 155 X 25
Читательская аудитория: Professional & vocational
Подзаголовок: With applications in r
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.



Pattern Recognition and Machine Learning

Автор: Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 6634 р.
Наличие на складе: Ожидается поступление.

Описание: The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.A forthcoming companion volume will deal with practical aspects of pattern recognition and machine learning, and will include free software implementations of the key algorithms along with example data sets and demonstration programs.Christopher Bishop is Assistant Director at Microsoft Research Cambridge, and also holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, and was recently elected Fellow of the Royal Academy of Engineering. The author's previous textbook "Neural Networks for Pattern Recognition" has been widely adopted.Coming soon:*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)*For instructors, worked solutions to remaining exercises from the Springer web site*Lecture slides to accompany each chapter*Data sets available for download

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: 6540 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.

Introduction to Time Series Using Stata

Автор: Becketti
Название: Introduction to Time Series Using Stata
ISBN: 1597181323 ISBN-13(EAN): 9781597181327
Издательство: Taylor&Francis
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Цена: 7732 р.
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Описание: Recent decades have witnessed explosive growth in new and powerful tools for timeseries analysis. These innovations have overturned older approaches to forecasting, macroeconomic policy analysis, the study of productivity and long-run economic growth, and the trading of financial assets. Familiarity with these new tools on time series is an essential skill for statisticians, econometricians, and applied researchers. Introduction to Time Series Using Stata provides a step-by-step guide to essential timeseries techniques—from the incredibly simple to the quite complex—and, at the same time, demonstrates how these techniques can be applied in the Stata statistical package. The emphasis is on an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced, and care is taken to highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a financial industry veteran with three decades of experience in academics, government, and private industry. Over the last two decades, Becketti has led proprietary research teams at several leading financial firms, responsible for the models underlying the valuation, hedging, and relative value analysis of some of the largest fixed-income portfolios in the world.

Introduction to High-Dimensional Statistics

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 5851 р.
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Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 16302 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Introduction to Nonextensive Statistical Mechanics

Автор: Constantino Tsallis
Название: Introduction to Nonextensive Statistical Mechanics
ISBN: 0387853588 ISBN-13(EAN): 9780387853581
Издательство: Springer
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Цена: 7863 р.
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Описание: Metaphors, generalizations and unifications are natural and desirable ingredients of the evolution of scientific theories and concepts. This book focuses on nonextensive statistical mechanics, a generalization of Boltzmann-Gibbs (BG) statistical mechanics, one of the greatest monuments of contemporary physics.

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 6164 р.
Наличие на складе: Поставка под заказ.

Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

An Introduction to Probability and Statistical Inference,

Автор: George G. Roussas
Название: An Introduction to Probability and Statistical Inference,
ISBN: 0125990200 ISBN-13(EAN): 9780125990202
Издательство: Elsevier Science
Цена: 9065 р.
Наличие на складе: Невозможна поставка.

Introduction to Statistical Physics

Автор: Salinas Silvio
Название: Introduction to Statistical Physics
ISBN: 0387951199 ISBN-13(EAN): 9780387951195
Издательство: Springer
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Цена: 8738 р.
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Описание: This textbook covers the basic principles of statistical physics and thermodynamics. The text is pitched at the level equivalent to first-year graduate studies or advanced undergraduate studies. After reviewing the basic probability theory of classical thermodynamics, the author addresses the standard topics of statistical physics.

An Introduction to Statistical Modeling of Extreme Values

Автор: Coles Stuart
Название: An Introduction to Statistical Modeling of Extreme Values
ISBN: 1852334592 ISBN-13(EAN): 9781852334598
Издательство: Springer
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Цена: 13089 р.
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Описание: Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.

Monte Carlo Simulation in Statistical Physics / An Introduction

Автор: Binder K., Heermann D.W.
Название: Monte Carlo Simulation in Statistical Physics / An Introduction
ISBN: 3540432213 ISBN-13(EAN): 9783540432210
Издательство: Springer
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Цена: 5138 р.
Наличие на складе: Нет в наличии.

Описание: Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. This fourth edition has been updated and a new chapter on Monte Carlo simulation of quantum-mechanical problems has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was the winner of the Berni J. Alder CECAM Award for Computational Physics 2001.

Probabilistic and Statistical Methods in Cryptology / An Introduction by Selected Topics

Автор: Neuenschwander Daniel
Название: Probabilistic and Statistical Methods in Cryptology / An Introduction by Selected Topics
ISBN: 3540220011 ISBN-13(EAN): 9783540220015
Издательство: Springer
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Цена: 4670 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Cryptology nowadays is one of the most important areas of applied mathematics, building on deep results and methods from various areas of mathematics. This text is devoted to the study of stochastic aspects of cryptology.Besides classical topics from cryptology, the author presents chapters on probabilistic prime number tests, factorization with quantum computers, random-number generators, pseudo-random-number generators, information theory, and the birthday paradox and meet-in-the-middle attack.In the light of the vast literature on stochastic results relevant for cryptology, this book is intended as an invitation and introduction for students, researchers, and practitioners to probabilistic and statistical issues in cryptology.


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