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| Le test RESET de Ramsey pour la forme fonctionnelle× | Régression polynomiale× | |
|---|---|---|
| Domaine≠ | Économétrie | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1969 | 2012 |
| Auteur d'origine≠ | James B. Ramsey | Montgomery, Peck & Vining (textbook treatment); classical least squares |
| Type≠ | Test for functional-form misspecification | Linear regression in transformed predictors |
| Source fondatrice≠ | Ramsey, J. B. (1969). Tests for specification errors in classical linear least-squares regression analysis. Journal of the Royal Statistical Society: Series B, 31(2), 350–371. DOI ↗ | Montgomery, D. C., Peck, E. A. & Vining, G. G. (2012). Introduction to Linear Regression Analysis. Wiley. ISBN: 978-0470542811 |
| Alias | RESET test, regression specification error test, Ramsey RESET fonksiyonel form testi | polynomial least squares, curvilinear regression, Polinom Regresyonu |
| Apparentées | 4 | 4 |
| Résumé≠ | The Ramsey RESET test, proposed by James Ramsey in 1969, is a general test for functional-form misspecification in a linear regression — for omitted nonlinear relationships between the response and the regressors. It adds powers of the fitted values to the model and checks whether they significantly improve the fit; if they do, the original linear specification has left systematic structure unexplained. | Polynomial regression is a regression method that models non-linear relationships by including squared and higher-degree terms of an explanatory variable, and it is a core tool of response surface analysis. As developed in Montgomery, Peck and Vining's Introduction to Linear Regression Analysis (2012), it remains linear in its parameters even though the fitted curve bends. |
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