Usporedite metode
Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.
| Fourier OLS (Fourier-augmentirani obični najmanji kvadrati)× | Regresija običnih najmanjih kvadrata (OLS)× | |
|---|---|---|
| Područje | Ekonometrija | Ekonometrija |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 2004 | 2019 |
| Tvorac≠ | Becker, Enders, and Hurn | Wooldridge (textbook treatment); classical least squares |
| Vrsta≠ | Augmented linear regression | Linear regression |
| Temeljni izvor≠ | Becker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899–906. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Drugi nazivi | Fourier OLS, Fourier-augmented OLS, trigonometric OLS, smooth structural break OLS | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Srodne≠ | 6 | 5 |
| Sažetak≠ | Fourier OLS is an OLS regression extended by adding low-frequency trigonometric (sine and cosine) terms to the regressor matrix. These Fourier components approximate smooth, gradual structural changes in the regression relationship over time without requiring knowledge of the number, timing, or form of the breaks. | 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). |
| ScholarGateSkup podataka ↗ |
|
|