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बहुपदीय लॉजिस्टिक प्रतिगमन×ऑर्डर्ड लॉजिस्टिक रिग्रेशन (ऑर्डर्ड लॉजिट/प्रोबिट)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19741980
प्रवर्तकMcFaddenMcCullagh (proportional odds / cumulative model)
प्रकारMultinomial logistic regressionCumulative ordinal regression
मौलिक स्रोतMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503McCullagh, P. (1980). Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B, 42(2), 109-142. DOI ↗
उपनामmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyonordinal logistic regression, proportional odds model, cumulative logit model, ordered probit
संबंधित54
सारांशMultinomial 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.Ordered logit is a cumulative regression model for an ordinal dependent variable, fitting a logit (or probit) link to the cumulative category probabilities. Developed in McCullagh's 1980 treatment of regression models for ordinal data, it is the standard tool for Likert-scale, rating, and ranked outcomes.
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