Introduction to Statistical Methods for Financial Models, Severini, Thomas A

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: 10480.00 р.
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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
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Цена: 8384.00 р.
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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: Zucchini
Название: Hidden Markov Models for Time Series
ISBN: 1482253836 ISBN-13(EAN): 9781482253832
Издательство: Taylor&Francis
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Цена: 14086.00 р.
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Описание: Hidden Markov Models (HMMs) remains a vibrant area of research in statistics, with many new applications appearing since publication of the first edition.

Автор: Dobson
Название: An Introduction to Generalized Linear Models
ISBN: 113874168X ISBN-13(EAN): 9781138741683
Издательство: Taylor&Francis
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Цена: 25265.00 р.
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Описание: An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, and a Postface on good statistical practice.

Автор: Lai, Tze Leung Xing, Haipeng
Название: Statistical models and methods for financial markets
ISBN: 1441926682 ISBN-13(EAN): 9781441926685
Издательство: Springer
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Цена: 10335.00 р.
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Описание: The authors here present statistical methods and models of importance to quantitative finance and links finance theory to market practice via statistical modeling and decision making. They provide basic statistical background as well as in-depth applications.

Автор: Lunn, David,
Название: The BUGS Book
ISBN: 1584888490 ISBN-13(EAN): 9781584888499
Издательство: Taylor&Francis
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Цена: 7042.00 р.
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Описание: Bayesian methods have become the widely used statistical methods for data analysis and modeling. The BUGS software has become the popular software for Bayesian analysis worldwide. This title provides a practical introduction to this program and its use. It covers the functionalities of BUGS, including prediction, missing data, and model criticism.

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 9645.00 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.

Автор: Efron
Название: An Introduction to the Bootstrap
ISBN: 0412042312 ISBN-13(EAN): 9780412042317
Издательство: Taylor&Francis
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Цена: 22968.00 р.
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Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.

Автор: Yang
Название: Introduction to Statistical Methods in Modern Genetics
ISBN: 9056991345 ISBN-13(EAN): 9789056991340
Издательство: Taylor&Francis
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Цена: 19906.00 р.
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Описание: Providing the required background in genetics, this book is useful for those looking to enter this arena. It includes some of the statistical tools important in genetics applications. It contains explanations, figures, and exercise sets in each chapter.

Автор: Severini
Название: Introduction To Statistical Methods
ISBN: 1138198374 ISBN-13(EAN): 9781138198371
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: This book introduces the use of statistical concepts and methods to model and analyze financial data, including the market model, the single-index model, and factor models. It contains detailed numerical examples using genuine financial data along with numerous exercises including both questions requiring analytic solutions and those requiring data analysis.

Автор: Tsiatis
Название: An Introduction To Dynamic Treatmen
ISBN: 1498769772 ISBN-13(EAN): 9781498769778
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: Precision medicine seeks to use data to construct principled, i.e., evidence-based, treatment strategies that dictate where, when, and to whom treatment should be applied. This book provides an accessible yet comprehensive introduction to statistical methodology for dynamic treatment regimes.

Автор: W.J.J. Rey
Название: Introduction to Robust and Quasi-Robust Statistical Methods
ISBN: 3540128662 ISBN-13(EAN): 9783540128663
Издательство: Springer
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Цена: 13275.00 р.
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