A Primer on Linear Models

John F. Monahan

ISBN 10: 1420062018 / ISBN 13: 9781420062014

Published by Chapman And Hall/CRC Mär 2008, 2008

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware - 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 methods. With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss-Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers. This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models. 302 pp. Englisch.

Seller Inventory # 9781420062014

Bibliographic Details

• Title: A Primer on Linear Models
• Publisher: Chapman And Hall/CRC Mär 2008
• Publication Date: 2008
• Language: English
• ISBN 10: 1420062018
• ISBN 13: 9781420062014
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 156H x 16D millimeters 234 millimeters width by 156 millimeters height by 16 millimeters depth
• Weight: 462 grams

About this title

Synopsis

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 methods.

With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss–Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers.

This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.

About the Author

John F. Monahan