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Statistical Methods for Ranking Data, Mayer Alvo; Philip L.H. Yu


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Автор: Mayer Alvo; Philip L.H. Yu
Название:  Statistical Methods for Ranking Data
ISBN: 9781493914708
Издательство: Springer
Классификация:
ISBN-10: 1493914707
Обложка/Формат: Hardcover
Страницы: 273
Вес: 0.58 кг.
Дата издания: 03.09.2014
Серия: Frontiers in Probability and the Statistical Sciences
Язык: English
Издание: 2014 ed.
Иллюстрации: 60 tables, black and white; 4 illustrations, color; 18 illustrations, black and white; xi, 273 p. 22 illus., 4 illus. in color.
Размер: 234 x 156 x 18
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data.


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: 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.

Statistical Learning for Biomedical Data

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
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Цена: 6494.00 р.
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Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

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: 27712.00 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.

Statistical models and methods for financial markets

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.

Statistical Methods for Ranking Data

Автор: Mayer Alvo; Philip L.H. Yu
Название: Statistical Methods for Ranking Data
ISBN: 1493947818 ISBN-13(EAN): 9781493947812
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data.

Ranking Of Multivariate Populations

Автор: Corain
Название: Ranking Of Multivariate Populations
ISBN: 1466505540 ISBN-13(EAN): 9781466505544
Издательство: Taylor&Francis
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Цена: 24499.00 р.
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Описание:

Ranking of Multivariate Populations: A Permutation Approach with Applications presents a novel permutation-based nonparametric approach for ranking several multivariate populations. Using data collected from both experimental and observation studies, it covers some of the most useful designs widely applied in research and industry investigations, such as multivariate analysis of variance (MANOVA) and multivariate randomized complete block (MRCB) designs.

The first section of the book introduces the topic of ranking multivariate populations by presenting the main theoretical ideas and an in-depth literature review. The second section discusses a large number of real case studies from four specific research areas: new product development in industry, perceived quality of the indoor environment, customer satisfaction, and cytological and histological analysis by image processing. A web-based nonparametric combination global ranking software is also described.

Designed for practitioners and postgraduate students in statistics and the applied sciences, this application-oriented book offers a practical guide to the reliable global ranking of multivariate items, such as products, processes, and services, in terms of the performance of all investigated products/prototypes.

Rankings and Preferences

Автор: Joaquim Pinto da Costa
Название: Rankings and Preferences
ISBN: 3662483432 ISBN-13(EAN): 9783662483435
Издательство: Springer
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Цена: 6986.00 р.
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Описание: In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis.We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections.

Probability Models and Statistical Analyses for Ranking Data

Автор: Michael A. Fligner; Joseph S. Verducci
Название: Probability Models and Statistical Analyses for Ranking Data
ISBN: 0387979204 ISBN-13(EAN): 9780387979205
Издательство: Springer
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Цена: 16769.00 р.
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Описание: In June of 1990, a conference was held on Probablity Models and Statisti- cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians.

Ranking and Prioritization for Multi-indicator Systems

Автор: Rainer Br?ggemann; Ganapati P. Patil
Название: Ranking and Prioritization for Multi-indicator Systems
ISBN: 1461429684 ISBN-13(EAN): 9781461429685
Издательство: Springer
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Цена: 21661.00 р.
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Описание: This book provides axioms of partial order and some basic material, for example consequences of "criss-crossing" of data profiles, the role of aggregations of the indicators and the powerful method of formal concept analysis.

Statistical Methods for Recommender Systems

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 7602.00 р.
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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.

Applied Linear Statistical Models with Student CD

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: 9265.00 р.
Наличие на складе: Поставка под заказ.

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.


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