เปรียบเทียบวิธี

	การถดถอยโลจิสติกส์หลายตัวแปร (Multinomial Logistic Regression)	การถดถอยพัวซงและทวินามเชิงลบ
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1974	1998
ผู้ริเริ่ม	McFadden	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
ประเภท	Multinomial logistic regression	Generalized linear model for count data
แหล่งต้นตำรับ	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	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
ชื่อเรียกอื่น	multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
ที่เกี่ยวข้อง	5	4
สรุป	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.	Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.