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Linear models with R, Faraway Julian J



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Цена: 14518р.
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Автор: Faraway Julian J
Название:  Linear models with R
Перевод названия: Джулиан Фарэвей: Линейные модели с помощью действительных чисел
ISBN: 9781439887332
Издательство: Taylor&Francis
Классификация:
ISBN-10: 1439887330
Обложка/Формат: Hardback
Страницы: 286
Вес: 0.57 кг.
Дата издания: 14.08.2014
Серия: Chapman & hall/crc texts in statistical science
Язык: English
Издание: 2 revised edition
Иллюстрации: 2/16- new cr file sent again - new version date 20160223; 94 illustrations, black and white
Размер: 243 x 157 x 18
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General
Ссылка на Издательство: Link
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Поставляется из: Англии



      Старое издание
Linear Models with R

Автор: Faraway, Julian J.
Название: Linear Models with R
ISBN: 1584884258 ISBN-13(EAN): 9781584884255
Издательство: Taylor&Francis
Цена: 9436 р.
Наличие на складе: Поставка под заказ.
Описание: Books on regression and the analysis of variance abound-many are introductory, many are theoretical. While most of them do serve a purpose, the fact remains that data analysis cannot be properly learned without actually doing it, and this means using a statistical software package. There are many of these to choose from as well, all with their particular strengths and weaknesses. Lately, however, one such package has begun to rise above the others thanks to its free availability, its versatility as a programming language, and its interactivity. That software is R.In the first book that directly uses R to teach data analysis, Linear Models with R focuses on the practice of regression and analysis of variance. It clearly demonstrates the different methods available and more importantly, in which situations each one applies. It covers all of the standard topics, from the basics of estimation to missing data, factorial designs, and block designs, but it also includes discussion on topics, such as model uncertainty, rarely addressed in books of this type. The presentation incorporates an abundance of examples that clarify both the use of each technique and the conclusions one can draw from the results. All of the data sets used in the book are available for download from http://www stat.lsa.umich.edu/ faraway/LMR/.The author assumes that readers know the essentials of statistical inference and have a basic knowledge of data analysis, linear algebra, and calculus. The treatment reflects his view of statistical theory and his belief that qualitative statistical concepts, while somewhat more difficult to learn, are just as important because they enable us to practice statistics rather than just talk about it.


Linear Models with R

Автор: Faraway, Julian J.
Название: Linear Models with R
ISBN: 1584884258 ISBN-13(EAN): 9781584884255
Издательство: Taylor&Francis
Рейтинг:
Цена: 9436 р.
Наличие на складе: Поставка под заказ.

Описание: Books on regression and the analysis of variance abound-many are introductory, many are theoretical. While most of them do serve a purpose, the fact remains that data analysis cannot be properly learned without actually doing it, and this means using a statistical software package. There are many of these to choose from as well, all with their particular strengths and weaknesses. Lately, however, one such package has begun to rise above the others thanks to its free availability, its versatility as a programming language, and its interactivity. That software is R.In the first book that directly uses R to teach data analysis, Linear Models with R focuses on the practice of regression and analysis of variance. It clearly demonstrates the different methods available and more importantly, in which situations each one applies. It covers all of the standard topics, from the basics of estimation to missing data, factorial designs, and block designs, but it also includes discussion on topics, such as model uncertainty, rarely addressed in books of this type. The presentation incorporates an abundance of examples that clarify both the use of each technique and the conclusions one can draw from the results. All of the data sets used in the book are available for download from http://www stat.lsa.umich.edu/ faraway/LMR/.The author assumes that readers know the essentials of statistical inference and have a basic knowledge of data analysis, linear algebra, and calculus. The treatment reflects his view of statistical theory and his belief that qualitative statistical concepts, while somewhat more difficult to learn, are just as important because they enable us to practice statistics rather than just talk about it.

Generalized Linear Models with Random Effects

Автор: Lee
Название: Generalized Linear Models with Random Effects
ISBN: 1584886315 ISBN-13(EAN): 9781584886310
Издательство: Taylor&Francis
Рейтинг:
Цена: 15609 р.
Наличие на складе: Поставка под заказ.

Описание: Presenting methods for fitting generalized linear models (GLMs) with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including meta-analysis of combining information over trials, analysis of frailty models for survival data, and analysis of spatial models with correlated errors. Punctuated by real examples from medicine, epidemiology, agriculture, and more, the book includes background material on likelihood inference and GLMs as well as topics such as frailty models. It computes methods using Genstat, with datasets and software available on CD and online, making it easy to test alternative analyses.

Plane Answers to Complex Questions / The Theory of Linear Models

Автор: Christensen Ronald
Название: Plane Answers to Complex Questions / The Theory of Linear Models
ISBN: 0387953612 ISBN-13(EAN): 9780387953618
Издательство: Springer
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Цена: 13358 р.
Наличие на складе: Нет в наличии.

Описание: This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate-level course. All of the standard topics are covered in depth: ANOVA, estimation including Bayesian estimation, hypothesis testing, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, variance component estimation, best linear and best linear unbiased prediction, collinearity, and variable selection. This new edition includes discussion of identifiability and its relationship to estimability, different approaches to the theories of testing parametric hypotheses and analysis of covariance, additional discussion of the geometry of least squares estimation and testing, new discussion of models for experiments with factorial treatment structures, and a new appendix on possible causes for getting test statistics that are so small as to be suspicious. This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The authors emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate- level course. All of the standard topics are covered in depth. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right. The author, Ronald Christensen, is a Professor of Statistics at the University of New Mexico.

Applying Generalized Linear Models

Автор: Lindsey
Название: Applying Generalized Linear Models
ISBN: 0387982183 ISBN-13(EAN): 9780387982182
Издательство: Springer
Рейтинг:
Цена: 13358 р.
Наличие на складе: Есть у поставщика 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.

Log-Linear Models and Logistic Regression

Автор: Christensen
Название: Log-Linear Models and Logistic Regression
ISBN: 0387982477 ISBN-13(EAN): 9780387982472
Издательство: Springer
Рейтинг:
Цена: 15882 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Serves as a reference and a graduate textbook in the area of categorical data analysis. This work includes data sets from engineering, education, sociology, and medicine.

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: 9799 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.

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: 8529 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.

Generalized Linear Models and Extensions, Third Edition

Автор: Hardin
Название: Generalized Linear Models and Extensions, Third Edition
ISBN: 1597181056 ISBN-13(EAN): 9781597181051
Издательство: Taylor&Francis
Рейтинг:
Цена: 9618 р.
Наличие на складе: Поставка под заказ.

Описание: This book presents a thorough examination of generalized linear model (GLM) estimation methods as well as the derivation of all major GLM families. Examined families include Gaussian, gamma, inverse Gaussian, binomial, Poisson, geometric, and negative binomial. The text also contains various models that have been developed on the basis of GLM theory, including GAM, ordered binomial models, multinomial logit and probit models, GEE and other quasi-likelihood models, fixed and random effects models, and random intercept and random parameter models. Using Stata, the book offers numerous examples to assist you in applying the models to your own data situations.

Methods and Applications of Linear Models: Regression and the Analysis of Variance, 2nd Edition

Автор: Ronald R. Hocking
Название: Methods and Applications of Linear Models: Regression and the Analysis of Variance, 2nd Edition
ISBN: 047123222X ISBN-13(EAN): 9780471232223
Издательство: Wiley
Цена: 14148 р.
Наличие на складе: Поставка под заказ.

Описание: The Second Edition has been rearranged and reorganized, as well as fully updated and expanded to cover new developments. Includes material on the AVE method and explains existing information in an even more user-friendly form. Includes additional exercises. Describes a general approach to the analysis of unbalanced mixed models Uses data-based approach to development and analysis. Data sets will be available on an FTP site

Автор: Joseph M. Hilbe and James W. Hardin
Название: Generalized Linear Models
ISBN: 1584887583 ISBN-13(EAN): 9781584887584
Издательство: Taylor&Francis
Цена: 7258 р.
Наличие на складе: Поставка под заказ.

Описание: "Generalized Linear Models: Theory and Applications" provides a comprehensive, practical introduction to generalized linear models that covers all of the main models and methods of estimation. Worked examples of real data are backed up by implementation in a range of software packages, including R, Stata, SAS, and LogiXact. The examples presented are taken predominantly from the health and social sciences, including health outcomes research, genetics, economics, education, and psychology.

The material is supported by a website with data sets, software links, and further examples.

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: 26729 р.
Наличие на складе: Есть у поставщика 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.

Linear Mixed Models for Longitudinal Data

Автор: Verbeke Geert, Molenberghs Geert
Название: Linear Mixed Models for Longitudinal Data
ISBN: 0387950273 ISBN-13(EAN): 9780387950273
Издательство: Springer
Рейтинг:
Цена: 15591 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, condional linear mid models).This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. How3ever, some other commercially available packages are discussed as well. Great care has been taken in presenting the data analyses in a software-independent fashion.Geert Verbeke is Assistant Professor at the Biostistical Centre of the Katholieke Universiteit Leuven in Belgium. He received the B.S. degree in mathematics (1989) from the Katholieke Universiteit Leuven, the M.S. in biostatistics (1992) from the Limburgs Universitair Centrum, and earned a Ph.D. in biostatistics (1995) from the Katholieke Universiteit Leuven. Dr. Verbeke wrote his dissertation, as well as a number of methodological articles, on various aspects of linear mixed models for longitudinal data analysis. He has held visiting positions at the Gerontology Research Center and the Johns Hopkins University.Geert Molenberghs is Assistant Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. He received the B.S. degree in mathematics (1988) and a Ph.D. in biostatistics (1993) from the Universiteit Antwerpen. Dr. Molenberghs published methodological work on the analysis of non-response in clinical and epidemiological studies. He serves as an associate editor for Biometrics, Applied Statistics, and Biostatistics, and is an officer of the Belgian Statistical Society. He has held visiting positions at the Harvard School of Public Health.


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