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| Holt-Winters hármas exponenciális simítás× | Regresszió Ordináris Legkisebb Négyzetes (OLS) módszerrel× | |
|---|---|---|
| Tudományterület | Ökonometria | Ökonometria |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 1960 | 2019 |
| Megalkotó≠ | Charles C. Holt and Peter R. Winters | Wooldridge (textbook treatment); classical least squares |
| Típus≠ | Exponential smoothing forecasting model | Linear regression |
| Alapmű≠ | Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Alternatív nevek | triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Kapcsolódó≠ | 4 | 5 |
| Összefoglaló≠ | Holt-Winters triple exponential smoothing is a forecasting model that extends Holt's double smoothing by adding a seasonal component, introduced by Peter Winters in 1960 building on Charles Holt's work. It tracks three evolving quantities — level, trend, and season — and combines them to forecast a continuous time series. | 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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