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Author: Murray A. Aitkin
Publisher: Oxford University Press, USA
Published: 2005
Total Pages: 584
ISBN-13: 9780198524137
DOWNLOAD EBOOK"This text examines the theory of statistical modelling with generalised linear models. It also looks at applications of the theory to practical problems, using the GLIM4 package"--Provided by publisher.
Author: Murray A. Aitkin
Publisher: Oxford University Press
Published: 1989
Total Pages: 390
ISBN-13: 9780198522034
DOWNLOAD EBOOKThe analysis of data by statistical modelling is becoming increasingly important. This book presents both the theory of statistical modelling with generalized linear models and the application of the theory to practical problems using the widely available package GLIM. The authors have takenpains to integrate the theory with many practical examples which illustrate the value of interactive statistical modelling. Throughout the book theoretical issues of formulating and simplifying models are discussed, as are problems of validating the models by the detection of outliers and influential observations. The book arises from short courses given at the University of Lancaster's Centre for Applied Statistics, with an emphasis on practical programming in GLIM and numerous examples. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential andWeibull distributions. A feature of the book is a detailed discussion of survival analysis. Statisticians working in a wide range of fields, including biomedical and social sciences, will find this book an invaluable desktop companion to aid their statistical modelling. It will also provide a text for students meeting the ideas of statistical modelling for the first time.
Author: Brian Francis
Publisher: Oxford University Press, USA
Published: 1993
Total Pages: 848
ISBN-13:
DOWNLOAD EBOOKIn statistics, fitting linear models to data is a general theme. This manual describes how GLIM 4--the popular software package--may be used for statistical analysis, including data manipulation and display, model fitting, and prediction. The manual has been divided into three distinct guides. The User Guide introduces and illustrates all the facilities in GLIM 4. Each chapter describes the directives relevant to a particular type of activity involved in the statistical modelling of data. The Modelling Guide presents a broad array of examples which comprise an effective introduction for new users. The Reference Guide contains a formal description of the syntax and semantics of the GLIM 4 language, of the data structures it handles, and of the directives provided, constituting a reference manual for the experienced user. This book is sure to be useful to research statisticians wherever GLIM is used.
Author: James K. Lindsey
Publisher:
Published: 1989
Total Pages: 178
ISBN-13:
DOWNLOAD EBOOKThis book shows how to apply log linear and logistic models to categorical data using GLIM. Each model is illustrated by a numerical example. All of the necessary programs in the GLIM macro language are supplied, as well as all data for the examples. The material has been the contents of a course for social science students, but would also be useful for applied statistics courses in such varied fields as medicine, geography, economics, biology ... It should also be extremely useful for research workers in these and other fields where such models are applied, since it provides a step by step explanation of how to analyse such data using these models. Almost all of the GLIM macro programs are new and have not previously appeared in the literature. Nor have many of the logistic/log linear models been applied using GLIM before.
Author: Daniel Powers
Publisher: Emerald Group Publishing
Published: 2008-11-13
Total Pages: 330
ISBN-13: 1781906599
DOWNLOAD EBOOKThis book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Author: James K. Lindsey
Publisher: Springer Science & Business Media
Published: 2008-01-15
Total Pages: 265
ISBN-13: 038722730X
DOWNLOAD EBOOKThis book describes how generalised linear modelling procedures can be used in many different fields, without becoming entangled in problems of statistical inference. The author shows the unity of many of the commonly used models and provides readers with a taste of many different areas, such as survival models, time series, and spatial analysis, and of their unity. As such, this book will appeal to applied statisticians and to scientists having a basic grounding in modern statistics. With many exercises at the end of each chapter, it will equally constitute an excellent text for teaching applied statistics students and non- statistics majors. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, being familiar at least with the analysis of the simpler normal linear models, regression and ANOVA.
Author: Esa Uusipaikka
Publisher: CRC Press
Published: 2008-07-25
Total Pages: 328
ISBN-13: 1420060384
DOWNLOAD EBOOKA Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data a
Author: P. McCullagh
Publisher: Routledge
Published: 2019-01-22
Total Pages: 536
ISBN-13: 1351445847
DOWNLOAD EBOOKThe 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 ot
Author: Ben Klemens
Publisher: Princeton University Press
Published: 2008-10-06
Total Pages: 471
ISBN-13: 1400828740
DOWNLOAD EBOOKModeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.
Author: Mick Crawley
Publisher: Wiley-Blackwell
Published: 1993-12-15
Total Pages: 392
ISBN-13: 9780632031566
DOWNLOAD EBOOKGLIM is one of the most powerful and efficient software packages for statistical analysis commercially avialable. The package can handle most of the analysis that ecologists are likely to carry out - regression, analysis of variance, log-linear models of counts, models in which the variance increases with the mean, models of survival, and much more. An initial encounter with GLIM can be a daunting experience for the beginner and a clear and comprehensive introduction to the package is essential. GLIM for Ecologists introduces the reader, step-by-step, to the methods of generalised linear modelling using the GLIM statistical language. Every ecologist intending to use the package will benefit from using the book as a guide through the initially impenetrable GLIM language. The book is appropriate for students and professionals alike and assumes that the reader has a working knowledge of linear regression, analysis of variance, significance tests, running programs on a desktop computer, and directory structure and file management in DOS. The book contains a wealth of exercises and examples and all of the data sets used in the book are available on disc
