Description: Generalized Linear Models by P. McCullagh, John A. Nelder This monograph deals with a class of statistical models that generalizes classical linear models to include many other models that have been found useful in statistical analysis. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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, and other applications.The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables.The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions.Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference. Author Biography P. McCullagh Table of Contents Preface, Introduction, Background, The Origins of Generalized Linear Models, Scope of the Rest of the Book, An Outline of Generalized Linear Models, Processes in Model Fitting, The Components of a Generalized Linear Model, Measuring the goodness of Fit, Residuals, An Algorithm for Fitting Generalized Linear Models, Models for Continuous Data with Constant Variance, Introduction, Error Structure, Systematic Component (Linear Predictor), Model Formulae for Linear Predictors, Aliasing, Estimation, Tables as Data, Algorithms for Least Squares, Selection of Covariates, Binary Data , Introduction, Binomial Distribution, Models for Binary Responses, Likelihood functions for Binary Data, Over-Dispersion, Example, Models for Polytomous Data, Introduction, Measurement scales, The Multinomical Distribution, Likelihood Functions, Over-Dispersion, Examples, Log-Linear Models, Introduction, Likelihood Functions, Examples, Log-Linear Models and Multinomial Response Models, Multiple responses, Example, Conditional Likelihoods, Introduction, Marginal and conditional Likelihoods, Hypergeometric Distributions, Some Applications Involving Binary data, Some Aplications Involving Polytomous Data, Models with Constant Coefficient of Variation, Introduction, The Gamma Distribution, Models with Gamma-distributed Observations, Examples, Quasi-Likelihood Functions, Introduction, Independent Observations, Dependent Observations, Optimal Estimating Functions, Optimality Criteria, Extended Quasi-Likelihood, Joint Modelling of Mean and Dispersion, Introduction, Model Specification, Interaction between Mean and Dispersion Effects, Extended Quasi-Likelihood as a Criterion, Adjustments of the Estimating Equations, Joint Optimum Estimating Equations, Example: The Production of Leaf-Springs for Trucks, Models with Additional Non-Linear Parameters, Introduction, Pa Review "... an important, useful book, well-written by two authorities in the field..."-Times Higher Education Supplement"... an enormous range of work is covered... represents, perhaps, the most important field of research in theoretical and practical statistics. For all statisticians working in this field, the book is essential."-Short Book Reviews"... this is a rich book; rich in theory, rich in examples, and rich in a statistical sense. I highly recommend it."-Biometrics"... a definitive and unified presentation...by the outstanding experts of this field."-Statistics"This is a wonderful book... Reading the book is like listening to a good lecturer. The authors present the material clearly, and they treat the reader with respect. There is a balance between discussion, mathematical presentation of models, and examples."-Technometrics"... a complete introduction to the topic in a single monograph... a very readable book that provides the reader with great insight into a vast array of data analysis techniques... -Siam Review"... a unique and useful text for intermediate undergraduate teaching."-THES Details ISBN0412317605 Short Title GENERALIZED LINEAR MODELS 2ND Language English Edition 2nd ISBN-10 0412317605 ISBN-13 9780412317606 Media Book DEWEY 519.5 Series Number 37 Illustrations Yes Year 1989 Imprint Chapman & Hall/CRC Pages 532 Format Hardcover Textbook 1 DOI 10.1604/9780412317606 UK Release Date 1989-08-01 AU Release Date 1989-08-01 NZ Release Date 1989-08-01 US Release Date 1989-08-01 Author John A. Nelder Publisher Taylor & Francis Ltd Edition Description 2nd edition Series Chapman & Hall/CRC Monographs on Statistics and Applied Probability Publication Date 1989-08-01 Alternative 9780367488406 Audience Tertiary & Higher Education Country of Publication United Kingdom We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:134662006;
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ISBN-13: 9780412317606
Book Title: Generalized Linear Models
Number of Pages: 532 Pages
Language: English
Publication Name: Generalized Linear Models
Publisher: Taylor & Francis Ltd
Publication Year: 1989
Subject: Mathematics
Item Height: 229 mm
Item Weight: 839 g
Type: Textbook
Author: P. Mccullagh, John A. Nelder
Item Width: 152 mm
Format: Hardcover