Linear Models Least Squares and Alternatives
The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
1995, 1995
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| Edition: | 1st ed. 1995 |
| Series: | Springer Series in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Introduction
- 2 Linear Models
- 3 The Linear Regression Model
- 4 The Generalized Linear Regression Model
- 5 Exact and Stochastic Linear Restrictions
- 6 Prediction Problems in the Generalized Regression Model
- 7 Sensitivity Analysis
- 8 Analysis of Incomplete Data Sets
- 9 Robust Regression
- 10 Models for Binary Response Variables
- A Matrix Algebra
- A.1 Introduction
- A.2 Trace of a Matrix
- A.3 Determinant of a Matrix
- A.4 Inverse of a Matrix
- A.5 Orthogonal Matrices
- A.6 Rank of a Matrix
- A.7 Range and Null Space
- A.8 Eigenvalues and Eigenvectors
- A.9 Decomposition of Matrices
- A.10 Definite Matrices and Quadratic Forms
- A.11 Idempotent Matrices
- A.12 Generalized Inverse
- A.13 Projectors
- A.14 Functions of Normally Distributed Variables
- A.15 Differentiation of Scalar Functions of Matrices
- A.16 Miscellaneous Results, Stochastic Convergence
- B Tables
- References