Compară metode

	Regresie logistică multinomială	Regresia prin metoda celor mai mici pătrate ordinare (OLS)
Domeniu	Econometrie	Econometrie
Familie	Regression model	Regression model
Anul apariției	1974	2019
Autorul original	McFadden	Wooldridge (textbook treatment); classical least squares
Tip	Multinomial logistic regression	Linear regression
Sursa seminală	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
Denumiri alternative	multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Înrudite	5	5
Rezumat	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).