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...

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Bibliographic Details
Main Authors: Rao, C.Radhakrishna, Toutenburg, Helge (Author)
Format: eBook
Language:English
Published: New York, NY Springer New York 1995, 1995
Edition:1st ed. 1995
Series:Springer Series in Statistics
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