Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Рамсея RESET для функциональной формы× | Регрессия методом обыкновенных наименьших квадратов (ОНМК)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1969 | 2019 |
| Автор метода≠ | James B. Ramsey | Wooldridge (textbook treatment); classical least squares |
| Тип≠ | Test for functional-form misspecification | Linear regression |
| Основополагающий источник≠ | 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 ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Другие названия≠ | RESET test, regression specification error test, Ramsey RESET fonksiyonel form testi | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Связанные≠ | 4 | 5 |
| Сводка≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateНабор данных ↗ |
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