Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| OLS jo-lineare (Minitë më të vogla të katrorëve jo-lineare)× | Regresioni me Mënyrën më të Vogël të Katrorëve (OLS)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 1974–1987 | 2019 |
| Krijuesi≠ | Gallant (1987); Wooldridge (2010) for econometric treatment | Wooldridge (textbook treatment); classical least squares |
| Lloji≠ | Nonlinear regression estimator | Linear regression |
| Burimi themelues≠ | Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Emërtime të tjera | nonlinear least squares, NLS, NLLS, nonlinear regression | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Të lidhura | 5 | 5 |
| Përmbledhja≠ | Nonlinear Ordinary Least Squares (NLS) estimates regression models in which the conditional mean function is nonlinear in the parameters. Like standard OLS it minimises the sum of squared residuals, but because no closed-form solution exists the estimator is found by iterative numerical optimisation. Under standard regularity conditions NLS is consistent and asymptotically normal. | 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). |
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