Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Παλινδρόμηση γάμμα (GLM)× | Παλινδρόμηση Ελαχίστων Τετραγώνων (OLS)× | |
|---|---|---|
| Πεδίο≠ | Στατιστική | Οικονομετρία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 1989 | 2019 |
| Δημιουργός≠ | McCullagh & Nelder (GLM framework) | Wooldridge (textbook treatment); classical least squares |
| Τύπος≠ | Generalized linear model | Linear regression |
| Θεμελιώδης πηγή≠ | 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 |
| Εναλλακτικές ονομασίες≠ | gamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Συναφείς≠ | 4 | 5 |
| Σύνοψη≠ | 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). |
| ScholarGateΣύνολο δεδομένων ↗ |
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