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Maximum Likelihood Estimation of Misspecified Dynamic Models Read chapter Read first chapter

1984 | OriginalPaper | Chapter

The Geometry of Model Selection in Regression

Author : Albert Verbeek

Published in: Misspecification Analysis

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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This paper deals with the selection of the linear model, i.e. the design matrix X, In linear regression model Ey=Xß. Special cases of this model selection problem are: the selection of predictor variables, selection of transformations, and selection of interactions to be included in the model. The combined process of model selection and parameter estimation is sketched in the classical Neyman-Pearson-Wald framework of mathematical statistics.

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Metadata
Title
The Geometry of Model Selection in Regression
Author
Albert Verbeek
Copyright Year
1984
Publisher
Springer Berlin Heidelberg
Book
Misspecification Analysis

Print ISBN: 978-3-540-13893-8

Electronic ISBN: 978-3-642-95461-0

Copyright Year: 1984

DOI
https://doi.org/10.1007/978-3-642-95461-0_2