Statistical Tools for Measuring Agreement, Lawrence Lin; A. S. Hedayat; Wenting Wu

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: 76850.00 T
Наличие на складе: Заказано в издательстве.
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: Nachtsheim;Neter;Kutner
Название: Applied Linear Statistical Models with Student CD
ISBN: 0071122214 ISBN-13(EAN): 9780071122214
Издательство: McGraw-Hill
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Цена: 61770.00 T
Наличие на складе: Нет в наличии.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 52800.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.

Автор: Martin A. Tanner
Название: Tools for Statistical Inference
ISBN: 0387946888 ISBN-13(EAN): 9780387946887
Издательство: Springer
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Цена: 93130.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. The third edition expands the discussion of many of the techniques discussed, includes additional examples, and adds exercise sets at the end of each chapter.

Автор: Sylvie Huet; Anne Bouvier; Marie-Anne Poursat; Emm
Название: Statistical Tools for Nonlinear Regression
ISBN: 1441923012 ISBN-13(EAN): 9781441923011
Издательство: Springer
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Цена: 75420.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.

Автор: Josselin, Jean-michel Le Maux, Benoit
Название: Statistical tools for program evaluation
ISBN: 3319528262 ISBN-13(EAN): 9783319528267
Издательство: Springer
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Цена: 102480.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A self-contained presentation of the statistical tools for evaluating public programs, as advocated by many governments, the World Bank, the European Union and the Organization for Economic Cooperation and Development, the book takes a step-by-step approach and many numerical illustrations to equip readers to handle program evaluation statistics.

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: 68900.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 60220.00 T
Наличие на складе: Нет в наличии.
Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Автор: James Gareth
Название: An Introduction to Statistical Learning
ISBN: 1461471370 ISBN-13(EAN): 9781461471370
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Невозможна поставка.
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.

Автор: Lunn, David,
Название: The BUGS Book
ISBN: 1584888490 ISBN-13(EAN): 9781584888499
Издательство: Taylor&Francis
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Цена: 46950.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: Guo Shenyang Y., Fraser Mark W.
Название: Propensity Score Analysis: Statistical Methods and Applications
ISBN: 1452235007 ISBN-13(EAN): 9781452235004
Издательство: Sage Publications
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Цена: 120390.00 T
Наличие на складе: Невозможна поставка.
Описание: Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and illustrates how it can be used for solving evaluation and causal-inference problems.

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 64300.00 T
Наличие на складе: Нет в наличии.
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.