Porovnať metódy
Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Multinomiálna logistická regresia× | Regresia metódou najmenších štvorcov (OLS)× | |
|---|---|---|
| Odbor | Ekonometria | Ekonometria |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1974 | 2019 |
| Tvorca≠ | McFadden | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Multinomial logistic regression | Linear regression |
| Pôvodný zdroj≠ | McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Ďalšie názvy | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Príbuzné | 5 | 5 |
| Zhrnutie≠ | Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category. | 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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