Model Selection and Simplification Using Lattices
AbstractThis paper shows how to cope with a problem of model selection and simplification using the principle of coherence (Gabriel (1969): A procedure involving testing a set of models ought not accept a model while rejecting a more general model). The mathematical lattice theory is used to define a partial ordering over the space of considered models. Several examples of partial ordering in large families of models are given along with a searching algorithm to determine the best model with respect to chosen criteria.
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Bibliographic InfoPaper provided by The Center for Economic Research and Graduate Education - Economic Institute, Prague in its series CERGE-EI Working Papers with number wp164.
Date of creation: Nov 2000
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model selection and simplification; principle of coherence; lattice of models; regression; ARMA models;
Other versions of this item:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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