পদ্ধতির তুলনা করুন

	নেগেটিভ বাইনোমিয়াল রিগ্রেশন	কোয়ান্টাইল রিগ্রেশন
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	2011	1978
প্রবর্তক	Hilbe (textbook treatment); generalized linear model framework	Koenker & Bassett
ধরন	Generalized linear model for count data	Conditional quantile regression
মৌলিক উৎস	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
অপর নাম	NB regression, NB2 regression, negatif binom regresyonu	conditional quantile regression, regression quantiles, Kantil Regresyon
সম্পর্কিত	4	5
সারসংক্ষেপ	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.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.