Abstract
A new method for testing linear restrictions in linear regression models is suggested. It allows to validate the linear restriction, up to a specified approximation error and with a specified error probability. The test relies on asymptotic normality of the test statistic, and therefore normality of the errors in the regression model is not required. In a simulation study the performance of the suggested method for model selection purposes, as compared to standard model selection criteria and the t-test, is examined. As an illustration we analyze the US college spending data from 1994.
| Dokumententyp: | Paper |
|---|---|
| Fakultät: | Mathematik, Informatik und Statistik > Statistik > Sonderforschungsbereich 386
Sonderforschungsbereiche > Sonderforschungsbereich 386 |
| Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
| URN: | urn:nbn:de:bvb:19-epub-1846-3 |
| Sprache: | Englisch |
| Dokumenten ID: | 1846 |
| Datum der Veröffentlichung auf Open Access LMU: | 11. Apr. 2007 |
| Letzte Änderungen: | 04. Nov. 2020 12:46 |

