Wiley, 2015. — 472 p. — (Wiley series in probability and statistics). — ISBN: 9781118730034 Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by...
Wiley, 2015. — 472 p. — (Wiley Series in Probability and Statistics). — ISBN: 9781118730034. Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by...
5th Edition. — Springer, 2020. — 539 p. — (Springer Texts in Statistics). — ISBN: 978-3-030-32096-6. 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,...
4th Edition. — Springer, 2011. — 516 p. — (Springer Texts in Statistics). — ISBN: 978-1-4419-9815-6, e-ISBN: 978-1-4419-9816-3. 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...
3rd Edition. — CRC Press, 2008. — 315 p. — ISBN: 1584889500, 9781584889502 Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian...
4th edition. — Boca Raton: CRC Press, 2018. — 378 p. — ISBN: 9781138741683, 113874168X. Scope Notation Distributions related to the Normal distribution Quadratic forms Estimation Exercises Examples Some principles of statistical modelling Notation and coding for explanatory variables Exercises Exponential family of distributions Properties of distributions in the exponential...
Springer Science+Business Media, 2018. — xx+562 p. — (Springer Texts in Statistics). — ISBN: 978-1-4419-0118-7. This textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed through the use of these data sets and numerous case studies. The...
N.-Y.: Springer, 2001. - 518p. The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. The second edition is extensively revised, especially in sections relating to Bayesian concepts. Modelling and Analysis of Cross-Sectional Data: A Review of Univariate Generalized Linear...
2nd ed. — CRC, 2016. — 413 p. — ISBN: 978-1-4987-2098-4. Start Analyzing a Wide Range of Problems Since the publication of the bestselling, highly recommended first edition, R has considerably expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second...
SAGE Publications, 2019. — 177 p. Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. Authors Jeff Gill and Michelle Torres provide examples using real data from multiple fields in the social sciences such as psychology, education, economics, and political science,...
Belmont: Wadsworth Publishing Company, 1976. — 716 p. In this book, Franklin A. Graybill integrates the linear statistical model within the context of analysis of variance, correlation and regression, and design of experiments. With topics motivated by real situations, it is a time tested, authoritative resource for experimenters, statistical consultants, and students.
Chapman & HALL. 1994 — 184 Pages. ISBN: 0412300400. In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric...
Sage Publications, 2024. — 205 p. Log-linear, logit and logistic regression models are the most common ways of analyzing data when (at least) the dependent variable is categorical. This volume shows how to compare coefficient estimates from regression models for categorical dependent variables in three typical research situations: (i) within one equation, (ii) between identical...
Stata Press, 2018. — 789 p. Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. GLM theory is predicated on the exponential family of distributions--a class so rich that it includes the commonly used logit, probit, and Poisson models. Although one can fit these models in Stata by using specialized commands (for...
4th Edition. — Stata Press, 2018. — 789 p. — ISBN13: 978-1-59718-225-6. Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. GLM theory is predicated on the exponential family of distributions-a class so rich that it includes the commonly used logit, probit, and Poisson models. Although one can fit these models in...
Boca Raton, USA: CRC Press, Taylor & Francis Group, 2018. — 539 p. — (Texts in Statistical Science Series). — ISBN: 1138578339. Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary...
CRC Press, 2023. — 234 p. — ISBN 9781032471235. Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume. The second volume complements the first, providing detailed solutions to the exercises in both volumes, thereby greatly enhancing its appeal for use in advanced...
World Scientific – 2003, 644 pages ISBN: 9810245920 Linear Models: An Integrated Approach aims to provide a clear and deep understanding of the general linear model using simple statistical ideas. Elegant geometric arguments are also invoked as needed and a review of vector spaces and matrices is provided to make the treatment self-contained. Complex, matrix-algebraic methods,...
Springer, 2007. — 257 p. — ISBN: 978-0387479415, e-ISBN: 978-0387479460. This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about...
2nd edition. — New York: Springer, 2021. — 352 p. This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear...
Hobokrn: Wiley, 2004. — 307 p. Generalised Least Squares adopts a concise and mathematically rigorous approach. It will provide an up-to-date self-contained introduction to the unified theory of generalized least squares estimations, adopting a concise and mathematically rigorous approach. The book covers in depth the 'lower and upper bounds approach', pioneered by the first...
CRC Press, 2010 -562 p. - Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles and theory is essential. Supported by a large number of examples, Linear Model Methodology provides a strong foundation in the theory of linear models and explores the latest developments in data analysis.
After...
Chapman & Hall/CRC, 2006. — 416 p. — ISBN: 1584886315, 978-1584886310. Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability (Book 106). Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear...
2nd edition. — New York: Chapman&Hall|CRC, 2018. — 467 p. This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the...
New York: Springer, 1989. — 172 p. The present text is the result of teaching a third year statistical course to undergraduate social science students. Besides their previous statistics courses, these students have had an introductory course in computer programming (FORTRAN, Pascal, or C) and courses in calculus and linear algebra, so that they may not be typical students of...
New York: Springer, 1992. — 300 p. The aim of this book is to present a survey of the many ways in which the statistical package GLIM may be used to model and analyze stochastic processes. Its emphasis is on using GLIM interactively to apply statistical techniques, and examples are drawn from a wide range of applications including medicine, biology, and the social sciences. It...
Springer Science & Business Media, 1997. — 256 p. — (Springer Texts in Statistics). Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview...
Hoboken: CRC Press, 2010. — 307 p. The likelihood principle General linear models Generalized linear models Mixed effects models Hierarchical models Real life inspired problems Supplement on the law of error propagation Some probability distributions List of symbols
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-032-50510-7. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall, 2ed, 1989 - 511 p. - The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering,...
N.-Y.: CRC Press, 2014. - 300p. Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides...
Boca Raton: Chapman & Hall/CRC, 2008. - 287p.
A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical...
Academic Press, 1996. — 228 p. — ISBN: 012508465X, 9780125084659. Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. Linear Models examines the subject from a mean model perspective, defining simple and easy-to-learn rules for building mean models, regression models, mean vectors,...
Wiley, 2006. — 410 p. — ISBN: 0471214884, 978-0471214885. A precise and accessible presentation of linear model theory, illustrated with data examples . Statisticians often use linear models for data analysis and for developing new statistical methods. Most books on the subject have historically discussed univariate, multivariate, and mixed linear models separately, whereas...
Printed in Sweden Studentlitteratur, Lund.
2002. — 244 pages.
ISBN: 9144041551.
Generalized Linear Models (GLM) is a general class of statistical models that includes many commonly used models as special cases. For example, the class of GLMs that includes linear regression, analysis of variance and analysis of covariance, is a special case of GLIMs. GLIMs also include...
Berlin: Springer, 2008. - 582p. Thoroughly revised and updated with the latest results, this Third Edition provides an up-to-date account of the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of...
2nd edition. — Springer, 1995. — 439 p. This book provides an up-to-date account of the theory and applications of linear models. It can be used as a text for courses in statistics at the graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions,...
Second Edition. — Wiley, 2008. — 688 p. — ISBN: 978-0-471-75498-5. The essential introduction to the theory and application of linear models — now in a valuable new edition. Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains...
Princeton: Princeton University, 2016. — 252 p. This course deals with statistical models for the analysis of quantitative and qualitative data, of the types usually encountered in social science research. The statistical methods studied are the general linear model for quantitative responses (including multiple regression, analysis of variance and analysis of covariance),...
Springer, 2023. — 436 p. — ISBN 9783031328008. Обобщенные линейные смешанные модели с приложениями в сельском хозяйстве и биологии This book offers an introduce-tion to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that...
Springer, 2023. — 436 p. — ISBN 9783031328008. Обобщенные линейные смешанные модели с приложениями в сельском хозяйстве и биологии This book offers an introduce-tion to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that...
Chapman and Hall/CRC, 2018. — 240 р. — (Chapman & Hall/CRC Interdisciplinary Statistics). — ISBN: 978-1498773133. Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to...
Springer, 2020. — 355 p. — (UNITEXT – La Matematica per il 3+2 Volume 124). — ISBN: 978-88-470-4001-4. Линейные Обобщенные модели Язык – Italiano Il volume fornisce un'introduzione a teoria e applicazioni dei modelli lineari generalizzati. Si presentano modelli di regressione per risposte continue, binarie, categoriali e di conteggio. Si offre anche un'introduzione ai modelli...
2nd Edition. — New Jersey, Canada: Wiley, 2017. — 696 p. — (Wiley Series in Probability and Statistics). — ISBN10: 1118952839. Provides an easy-to-understand guide to statistical linear models and its uses in data analysis This book defines a broad spectrum of statistical linear models that is useful in the analysis of data. Considerable rewriting was done to make the book more...
New York: Springer, 2015. - 205p. This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to...
Cambridge: Cambridge University Press, 2024. — 306 p. An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) – one of the most important classes of distributional regression. Taking a broad...
Hoboken: CRC Press, 2012. — 547 p. The Big Picture Modeling Basics Design Matters Setting the Stage Estimation and Inference Essentials Estimation Inference, Part I: Model Effects Inference, Part II: Covariance Components Working with GLMMs Treatment and Explanatory Variable Structure Multilevel Models Best Linear Unbiased Prediction Rates and Proportions Counts Time-to-Event...
2nd ed. — CRC Press, 2024. — 670 p. — (Chapman & Hall/CRC Texts in Statistical Science). — ISBN 1498755569. Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling,...
Springer, 2020. — 350 p. — ISBN: 978-3-030-52073-1. This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses, estimability, best linear unbiased estimation and prediction, ANOVA, confidence intervals, simultaneous confidence intervals, hypothesis testing, and variance component estimation. The models...
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