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Detalles bibliogr�ficos

T�tulo: An Introduction to Generalized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
Editor: Chapman and Hall/CRC
Fecha de publicaci�n: 2001
Idioma: Ingl�s
ISBN 10: 1584881658
ISBN 13: 9781584881650
Encuadernaci�n: Encuadernaci�n de tapa blanda
Edici�n: 2� Edici�n
Estado: Very Good
Peso: 340 gramos

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Sinopsis

Generalized linear models provide a unified theoretical and conceptual framework for many of the most commonly used statistical methods. In the ten years since publication of the first edition of this bestselling text, great strides have been made in the development of new methods and in software for generalized linear models and other closely related models. Thoroughly revised and updated, An Introduction to Generalized Linear Models, Second Edition continues to initiate intermediate students of statistics, and the many other disciplines that use statistics, in the practical use of these models and methods. The new edition incorporates many of the important developments of the last decade, including survival analysis, nominal and ordinal logistic regression, generalized estimating equations, and multi-level models. It also includes modern methods for checking model adequacy and examples from an even wider range of application. Statistics can appear to the uninitiated as a collection of unrelated tools. An Introduction to Generalized Linear Models, Second Edition illustrates how these apparently disparate methods are examples or special cases of a conceptually simple structure based on the exponential family of distribution, maximum likelihood estimation, and the principles of statistical modelling.

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..." a unique and useful text for intermediate undergraduate teaching." -Times Higher Education Supplement "I liked Dobson's basic and relatively brief presentationThanks go to the publisher for the softcover edition and attendant modest price, another of the book's virtues besides its brevity. These attributes make this book a recommended purchase for those who need a book on logistic regression. It is a good place to start." -Technometrics, November 2002

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