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Multinomiale Logistische Regression×Methode der kleinsten Quadrate (OLS)×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr19742019
UrheberMcFaddenWooldridge (textbook treatment); classical least squares
TypMultinomial logistic regressionLinear regression
Wegweisende QuelleMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Aliasnamenmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyonordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Verwandt55
ZusammenfassungMultinomial 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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ScholarGateMethoden vergleichen: Multinomial Logit · OLS Regression. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare