विधियों की तुलना करें

	बोनस-मालस प्रणाली (Bonus-Malus System)	ऋणात्मक द्विपद समाश्रयण (Negative Binomial Regression)
क्षेत्र	बीमांकिक विज्ञान	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1995	2011
प्रवर्तक	Jean Lemaire	Hilbe (textbook treatment); generalized linear model framework
प्रकार	Actuarial experience-rating model	Generalized linear model for count data
मौलिक स्रोत	Lemaire, J. (1995). Bonus-Malus Systems in Automobile Insurance. Kluwer Academic Publishers. ISBN: 978-0-7923-9545-5	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.
उपनाम	No-Claim Discount System, Merit Rating System, Experience Rating in Automobile Insurance, Prim-Ceza Sistemi	NB regression, NB2 regression, negatif binom regresyonu
संबंधित	2	4
सारांश	A Bonus-Malus System (BMS) is an actuarial experience-rating mechanism used primarily in automobile insurance to adjust individual policyholders' premiums based on their personal claim history. Policyholders who remain claim-free receive premium discounts (bonus), while those who file claims are penalised with surcharges (malus). The framework was comprehensively formalised and analysed by Jean Lemaire in his landmark 1995 monograph, which remains the definitive reference for the design and evaluation of such systems worldwide.	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.