Linear Models: Least Squares and Alternatives
C.Radhakrishna Rao, Helge Toutenburg, Christian Heumann, Thomas Nittner, Sandro Scheid
Provides a current account of the theory and applications of linear models. Presents a unified theory of inference from linear models with minimal assumptions through least squares theory, and using alternative methods of estimation and testing based on convex loss functions and general estimating equations.
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