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Logistická regrese×Multinomická logistická regrese×
OborStatistika ve výzkumuEkonometrie
RodinaProcess / pipelineRegression model
Rok vzniku19581974
TvůrceDavid Roxbee CoxMcFadden
TypMethodMultinomial logistic regression
Původní zdrojCox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗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
Další názvylogit model, binomial logistic regression, LRmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Příbuzné35
ShrnutíLogistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.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.
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ScholarGatePorovnat metody: Logistic Regression · Multinomial Logit. Získáno 2026-06-17 z https://scholargate.app/cs/compare