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| Gama regresija (GLM)× | Regresija običnih najmanjih kvadrata (OLS)× | |
|---|---|---|
| Područje≠ | Statistika | Ekonometrija |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 1989 | 2019 |
| Tvorac≠ | McCullagh & Nelder (GLM framework) | Wooldridge (textbook treatment); classical least squares |
| Vrsta≠ | Generalized linear model | Linear regression |
| Temeljni izvor≠ | McCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Drugi nazivi≠ | gamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Srodne≠ | 4 | 5 |
| Sažetak≠ | Gamma regression is a generalized linear model that uses the gamma distribution to model a positive, right-skewed continuous outcome. Developed within the GLM framework of McCullagh and Nelder (1989), it is an alternative to ordinary linear regression for variables such as health-care costs, durations, and income. | 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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