Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Tobit Gecensureerd Regressiemodel× | Gewone Kleinste Kwadraten (GKK) Regressie× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1958 | 2019 |
| Grondlegger≠ | James Tobin | Wooldridge (textbook treatment); classical least squares |
| Type≠ | Censored regression (limited dependent variable) | Linear regression |
| Oorspronkelijke bron≠ | Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Aliassen≠ | censored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Verwant≠ | 4 | 5 |
| Samenvatting≠ | The Tobit model is a regression for outcomes that are censored at a threshold, estimating the relationship by maximum likelihood. Introduced by James Tobin in 1958, it addresses the pile-up of observations at a limit (typically zero) in data such as spending, wages, or duration. | 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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