विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| रैम्से रीसेट टेस्ट फॉर फंक्शनल फॉर्म× | बहुपद समाश्रयण (Polynomial Regression)× | |
|---|---|---|
| क्षेत्र≠ | अर्थमिति | सांख्यिकी |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1969 | 2012 |
| प्रवर्तक≠ | James B. Ramsey | Montgomery, Peck & Vining (textbook treatment); classical least squares |
| प्रकार≠ | Test for functional-form misspecification | Linear regression in transformed predictors |
| मौलिक स्रोत≠ | 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 |
| उपनाम | RESET test, regression specification error test, Ramsey RESET fonksiyonel form testi | polynomial least squares, curvilinear regression, Polinom Regresyonu |
| संबंधित | 4 | 4 |
| सारांश≠ | 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. |
| ScholarGateडेटासेट ↗ |
|
|