Linear Models by Shayle R Searle

Linear Models by Shayle R Searle

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Linear Models by Shayle R Searle

WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

This book] provides an excellent discussion of the methodology and interpretation of linear models analysis of unbalanced data (data having unequal numbers of observations in the subclasses), generally without matrices?the author does an excellent job of emphasizing the more practical nature of the book. Highly recommended for graduate and undergraduate libraries.
?Choice

This is a very comprehensive text, aimed at both students studying linear-model theory and practicing statisticians who require an understanding of the model-fitting procedures incorporated in statistical packages?This book should be considered as a text for college courses as it provides a clearly presented and thorough treatment of linear models. It will also be useful to any practicing statistician who has to analyze unbalanced data, perhaps arising from surveys, and wishes to understand the output from model-fitting procedures and the discrepancies in analysis from one recognized package to another.
?Biometrics

This newly available and affordably priced paperback version of Linear Models for Unbalanced Data offers a presentation of the fundamentals of linear statistical models unique in its total devotion to unbalanced data and its emphasis on the up-to-date cell means model approach to linear models for unbalanced data. Topic coverage includes cell means models, 1-way classification, nested classifications, 2-way classification with some-cells-empty data, models with covariables, matrix algebra and quadratic forms, linear model theory, and much more.
SHAYLE R. SEARLE, PhD, is Professor Emeritus of Biometry at Cornell University. He is the author of Linear Models, Linear Models for Unbalanced Data, and Matrix Algebra Useful for Statistics, all from Wiley.

GEORGE CASELLA, PhD, is Professor and Chair of the Department of Statistics at the University of Florida. His research interests include decision theory and statistical confidence.

CHARLES E. McCULLOCH, PhD, is Professor of Biostatistics at the University of California, San Francisco. He is the author of numerous scientific publications on biometrics and bio-logical statistics. He is a coauthor, with Shayle R. Searle, of Generalized, Linear, and Mixed Models (Wiley 2001).

SKU Nicht verfügbar
ISBN 13 9780471769507
ISBN 10 0471769509
Titel Linear Models
Autor Shayle R Searle
Serie Probability And Mathematical Statistics S
Buchzustand Nicht verfügbar
Bindungsart Hardback
Verlag John Wiley and Sons Ltd
Erscheinungsjahr 1971-01-15
Seitenanzahl 556
Hinweis auf dem Einband Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis Nicht verfügbar