Comparer des méthodes

	Le test RESET de Ramsey pour la forme fonctionnelle	Régression linéaire multiple
Domaine	Économétrie	Statistique
Famille	Regression model	Regression model
Année d'origine	1969	1886
Auteur d'origine	James B. Ramsey	Francis Galton; formalized by Karl Pearson
Type	Test for functional-form misspecification	Parametric linear model
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.	Galton, F. (1886). Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263.
Alias	RESET test, regression specification error test, Ramsey RESET fonksiyonel form testi	MLR, OLS regression, multiple regression, linear regression with multiple predictors
Apparentées	4	8
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.	Multiple linear regression (MLR) is a parametric regression model that expresses a continuous outcome as a weighted linear combination of two or more predictor variables plus a random error term. The unknown weights (regression coefficients) are estimated by ordinary least squares (OLS), which minimises the sum of squared residuals. The method traces to Francis Galton's 1886 work on hereditary stature and was placed on firm mathematical footing by Karl Pearson; Draper and Smith's 1966 textbook established it as the standard framework for applied regression.