विधियों की तुलना करें

	बहुपदीय लॉजिस्टिक प्रतिगमन	ऋणात्मक द्विपद समाश्रयण (Negative Binomial Regression)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1974	2011
प्रवर्तक	McFadden	Hilbe (textbook treatment); generalized linear model framework
प्रकार	Multinomial logistic regression	Generalized linear model for count data
मौलिक स्रोत	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	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.
उपनाम	multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon	NB regression, NB2 regression, negatif binom regresyonu
संबंधित	5	4
सारांश	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.	Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.