Automatic selection for non-linear models
© 2012 Springer-Verlag London Limited.Our strategy for automatic selection in potentially non-linear processes is: test for non-linearity in the unrestricted linear formulation; if that test rejects, specify a general model using polynomials, to be simplified to a minimal congruent representation; f...
| Autores principales: | , |
|---|---|
| Formato: | Book section |
| Publicado: |
Springer London
2011
|
| Sumario: | © 2012 Springer-Verlag London Limited.Our strategy for automatic selection in potentially non-linear processes is: test for non-linearity in the unrestricted linear formulation; if that test rejects, specify a general model using polynomials, to be simplified to a minimal congruent representation; finally select by encompassing tests of specific non-linear forms against the selected model. Non-linearity poses many problems: extreme observations leading to non-normal (fat-tailed) distributions; collinearity between non-linear functions; usually more variables than observations when approximating the non-linearity; and excess retention of irrelevant variables; but solutions are proposed. A returns-to-education empirical application demonstrates the feasibility of the non-linear automatic model selection algorithm Autometrics. |
|---|