পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Bonus-Malus System× | নেগেটিভ বাইনোমিয়াল রিগ্রেশন× | |
|---|---|---|
| ক্ষেত্র≠ | বীমাঙ্কন বিজ্ঞান | অর্থমিতি |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1995 | 2011 |
| প্রবর্তক≠ | Jean Lemaire | Hilbe (textbook treatment); generalized linear model framework |
| ধরন≠ | Actuarial experience-rating model | Generalized linear model for count data |
| মৌলিক উৎস≠ | 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. DOI ↗ |
| অপর নাম≠ | No-Claim Discount System, Merit Rating System, Experience Rating in Automobile Insurance, Prim-Ceza Sistemi | NB regression, NB2 regression, negatif binom regresyonu |
| সম্পর্কিত≠ | 2 | 4 |
| সারসংক্ষেপ≠ | 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. |
| ScholarGateডেটাসেট ↗ |
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