
Linear Models: An Integrated Approach
An Integrated Approach
- 644 pages
- English
- PDF
- Available on iOS & Android
About this book
Linear Models: An Integrated Approach aims to provide a clear and deep understanding of the general linear model using simple statistical ideas. Elegant geometric arguments are also invoked as needed and a review of vector spaces and matrices is provided to make the treatment self-contained. Complex, matrix-algebraic methods, such as those used in the rank-deficient case, are replaced by statistical proofs that are more transparent and that show the parallels with the simple linear model.This book has the following special features:⢠Use of simple statistical ideas such as linear zero functions and covariance adjustment to explain the fundamental as well as advanced concepts⢠Emphasis on the statistical interpretation of complex algebraic results⢠A thorough treatment of the singular linear model, including the case of multivariate response⢠A unified discussion on models with a partially unknown dispersion matrix, including mixed-effects/variance-components models and models for spatial and time series data⢠Insight into updates on the linear model and their connection with diagnostics, design, variable selection, the Kalman filter, etc.⢠An extensive discussion on the foundations of linear inference, along with linear alternatives to least squares⢠Coverage of other special topics, such as collinearity, stochastic and inequality constraints, misspecified models, etc.⢠Simpler proofs of numerous known results⢠Pointers to current research through examples and exercises
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Information
Table of contents
- Preface
- Contents
- Glossary of Abbreviations
- Glossary of Matrix Notations
- Chapter 1 Introduction
- Chapter 2 Review of Linear Algebra
- Chapter 3 Review of Statistical Results
- Chapter 4 Estimation in the Linear Model
- Chapter 5 Further Inference in the Linear Model
- Chapter 6 Analysis of Variance in Basic Designs
- Chapter 7 General Linear Model
- Chapter 8 Misspecified or Unknown Dispersion
- Chapter 9 Updates in the General Linear Model
- Chapter 10 Multivariate Linear Model
- Chapter 11 Linear Inference ā Other Perspectives
- Solutions to Odd-Numbered Exercises
- Bibliography and Author Index
- Index