方法对比

	可信度理论	负二项回归
领域	精算学	计量经济学
方法族	Regression model	Regression model
起源年份	1967	2011
提出者	Hans Bühlmann	Hilbe (textbook treatment); generalized linear model framework
类型	Weighted linear blend of individual and collective experience	Generalized linear model for count data
开创性文献	Bühlmann, H. (1967). Experience rating and credibility. ASTIN Bulletin, 4(3), 199–207.	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.
别名	Bühlmann Credibility, Experience Rating, Linear Credibility Estimator, Güvenilirlik Teorisi	NB regression, NB2 regression, negatif binom regresyonu
相关	3	4
摘要	Credibility Theory is an actuarial framework for estimating the pure premium of an individual risk by blending its own observed loss experience with the collective (portfolio) mean. Introduced by Hans Bühlmann in 1967, the method derives the optimal linear combination—the credibility-weighted premium—that minimises mean squared error. It extends classical experience rating to a rigorous statistical footing rooted in Bayesian and linear estimation principles.	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.