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Generalized Additive Models: An Introduction with R, Wood, Simon



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Автор: Wood, Simon
Название:  Generalized Additive Models: An Introduction with R
Перевод названия: Саймон Вуд: Обобщающие аддитивные модели
ISBN: 9781584884743
Издательство: Taylor&Francis
Классификация:
ISBN-10: 1584884746
Обложка/Формат: Hardback
Страницы: 410
Вес: 0.703 кг.
Дата издания: 27.02.2006
Серия: Texts in statistical science
Язык: English
Иллюстрации: 103 black & white illustrations
Размер: 235 x 156 x 27
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Англии
Дополнительное описание: Дата издания: 2005





      Новое издание
Generalized Additive Models

Автор: Wood
Название: Generalized Additive Models
ISBN: 1498728332 ISBN-13(EAN): 9781498728331
Издательство: Taylor&Francis
Цена: 9486 р.
Наличие на складе: Есть у поставщикаПоставка под заказ.
Описание: The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models. The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study. Simon N. Wood is a professor of Statistical Science at the University of Bristol, UK, and author of the R package mgcv.


Generalized Additive Models

Автор: Wood
Название: Generalized Additive Models
ISBN: 1498728332 ISBN-13(EAN): 9781498728331
Издательство: Taylor&Francis
Рейтинг:
Цена: 9486 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models. The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study. Simon N. Wood is a professor of Statistical Science at the University of Bristol, UK, and author of the R package mgcv.

Generalized Linear Models: With Applications in Engineering and the Sciences

Автор: Raymond H. Myers
Название: Generalized Linear Models: With Applications in Engineering and the Sciences
ISBN: 0471355739 ISBN-13(EAN): 9780471355731
Издательство: Wiley
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Цена: 13681 р.
Наличие на складе: Поставка под заказ.

Описание: This volume serves as an introductory text or reference on Generalized Linear Models (GLMs). The range of theoretical topics and applications give this book broad appeal to practicing professionals in a variety of fields and as a textbook for students in regression courses.

Generalized, Linear, and Mixed Models

Автор: Charles E. McCulloch
Название: Generalized, Linear, and Mixed Models
ISBN: 047119364X ISBN-13(EAN): 9780471193647
Издательство: Wiley
Цена: 9756 р.
Наличие на складе: Поставка под заказ.

Описание: Wiley Series in Probability and Statistics

An Introduction to Generalized Linear Models, Third Edition

Название: An Introduction to Generalized Linear Models, Third Edition
ISBN: 1584889500 ISBN-13(EAN): 9781584889502
Издательство: Taylor&Francis
Рейтинг:
Цена: 6461 р.
Наличие на складе: Поставка под заказ.

Описание: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.

Introduction to General and Generalized Linear Models

Название: Introduction to General and Generalized Linear Models
ISBN: 1420091557 ISBN-13(EAN): 9781420091557
Издательство: Taylor&Francis
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Цена: 8250 р.
Наличие на складе: Поставка под заказ.

Описание: Since the mathematics behind generalized linear models is often difficult to follow while the mathematics behind general linear models is well understood, this text describes the methodology behind both models in a parallel setup.

Explanatory Item Response Models / A Generalized Linear and Nonlinear Approach

Автор: Boeck Paul De, Wilson Mark
Название: Explanatory Item Response Models / A Generalized Linear and Nonlinear Approach
ISBN: 0387402756 ISBN-13(EAN): 9780387402758
Издательство: Springer
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Цена: 17324 р.
Наличие на складе: Поставка под заказ.

Описание: This edited volume gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. The new framework allows the domain of item response models to be co-ordinated and broadened to emphasize their explanatory uses beyond their standard descriptive uses. The basic explanatory principle is that item responses can be modeled as a function of predictors of various kinds. The predictors can be (a) characteristics of items, of persons, and of combinations of persons and items; (b) observed or latent (of either items or persons); and they can be (c) latent continuous or latent categorical. In this way a broad range of models is generated, including a wide range of extant item response models as well as some new ones. Within this range, models with explanatory predictors are given special attention in this book, but we also discuss descriptive models. Note that the term "item responses" does not just refer to the traditional "test data," but are broadly conceived as categorical data from a repeated observations design. Hence, data from studies with repeated observations experimental designs, or with longitudinal designs, may also be modelled.The book starts with a four-chapter section containing an introduction to the framework. The remaining chapters describe models for ordered-category data, multilevel models, models for differential item functioning, multidimensional models, models for local item dependency, and mixture models. It also includes a chapter on the statistical background and one on useful software. In order to make the task easier for the reader, a unified approach to notation and model description is followed throughout the chapters, and a single data set is used in most examples to make it easier to see how the many models are related. For all major examples, computer commands from the SAS package are provided that can be used to estimate the results for each model. In addition, sample commands are provided for other major computer packages.Paul De Boeck is Professor of Psychology at K.U. Leuven (Belgium), and Mark Wilson is Professor of Education at UC Berkeley (USA). They are also co-editors (along with Pamela Moss) of a new journal entitled Measurement: Interdisciplinary Research and Perspectives. The chapter authors are members of a collaborative group of psychometricians and statisticians centered on K.U. Leuven and UC Berkeley.From the reviews:"[It is] full of nice features to make it widely useable by practitioners and applied statisticians alike, and it does a wonderful job connecting psychometrics to the field of statisitcs." Deniz Senturk for Technometrics, November 2006

Multivariate Statistical Modelling Based on Generalized Linear Models

Автор: Fahrmeir Ludwig, Tutz Gerhard, Hennevogl W.
Название: Multivariate Statistical Modelling Based on Generalized Linear Models
ISBN: 0387951873 ISBN-13(EAN): 9780387951874
Издательство: Springer
Рейтинг:
Цена: 20789 р.
Наличие на складе: Поставка под заказ.

Описание: The first edition of Multivariate Statistical Modelling provided an extension of classical models for regression, time series, and longitudinal data to a much broader class including categorical data and smoothing concepts. Generalized linear modesl for univariate and multivariate analysis build the central concept, which for the modelling of complex data is widened to much more general modelling approaches. The primary aim of the new edition is to bring the book up-to-date and to reflect the major new developments over the past years. The authors give a detailed introductory survey of the subject based on the alaysis of real data drawn from a variety of subjects, including the biological sciences, economics, and the social sciences. Technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. The appendix serves as a reference or brief tutorial for the concepts of EM algorithm, numberical integration, MCMC and others. The topics covered inlude: Models for multi-categorial responses, model checking, semi- and nonparametric modelling, time series and longitudinal data, random effects models, state-space models, and survival analysis. The authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, this book is ideally suited for applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis from econometrics, biometrics and the social sciences.

Applying Generalized Linear Models

Автор: Lindsey
Название: Applying Generalized Linear Models
ISBN: 0387982183 ISBN-13(EAN): 9780387982182
Издательство: Springer
Рейтинг:
Цена: 10389 р.
Наличие на складе: Поставка под заказ.

Описание: Generalized linear models have applications in many areas, including social science and life science. This book serves as a reference and advanced text for students interested in the applications of statistics.

Generalized Linear Models for Insurance Data

Автор: Piet de Jong
Название: Generalized Linear Models for Insurance Data
ISBN: 0521879140 ISBN-13(EAN): 9780521879149
Издательство: Cambridge Academ
Рейтинг:
Цена: 11502 р.
Наличие на складе: Поставка под заказ.

Описание: This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

Multivariate generalized linear mixed models using r

Автор: Berridge, Damon M. Crouchley, Robert
Название: Multivariate generalized linear mixed models using r
ISBN: 1439813264 ISBN-13(EAN): 9781439813263
Издательство: Taylor&Francis
Рейтинг:
Цена: 11686 р.
Наличие на складе: Поставка под заказ.

Описание: To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). It includes chapters that cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs).

Generalized linear models

Название: Generalized linear models
ISBN: 0470454636 ISBN-13(EAN): 9780470454633
Издательство: Wiley
Рейтинг:
Цена: 16775 р.
Наличие на складе: Поставка под заказ.

Описание: Maintaining the same nontechnical approach as its acclaimed predecessor, this second edition of Generalized Linear Models is now thoroughly extended to include the latest developments in the field, the most relevant computational approaches, and the most relevant examples from the fields of engineering and physical sciences.

Applied regression analysis and generalized linear models

Автор: Fox, Dr. John (mcmaster University, Hamilton, Onta
Название: Applied regression analysis and generalized linear models
ISBN: 0761930426 ISBN-13(EAN): 9780761930426
Издательство: Sage Publications
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Цена: 8354 р.
Наличие на складе: Поставка под заказ.

Описание: Gives coverage to regression models such as: generalized linear models; limited-dependent-variable-models; mixed models and Cox regression, among other methods.


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