ScholarGate
Asistents

Salīdzināt metodes

Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Bonus-Malus sistēma×Kredibilittes teorija×
NozareAktuārā zinātneAktuārā zinātne
SaimeRegression modelRegression model
Izcelsmes gads19951967
AutorsJean LemaireHans Bühlmann
TipsActuarial experience-rating modelWeighted linear blend of individual and collective experience
PirmavotsLemaire, J. (1995). Bonus-Malus Systems in Automobile Insurance. Kluwer Academic Publishers. ISBN: 978-0-7923-9545-5Bühlmann, H. (1967). Experience rating and credibility. ASTIN Bulletin, 4(3), 199–207. DOI ↗
Citi nosaukumiNo-Claim Discount System, Merit Rating System, Experience Rating in Automobile Insurance, Prim-Ceza SistemiBühlmann Credibility, Experience Rating, Linear Credibility Estimator, Güvenilirlik Teorisi
Saistītās23
KopsavilkumsA 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.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.
ScholarGateDatu kopa
  1. v1
  2. 1 Avoti
  3. PUBLISHED
  1. v1
  2. 1 Avoti
  3. PUBLISHED

Doties uz meklēšanu Lejupielādēt slaidus

ScholarGateSalīdzināt metodes: Bonus-Malus System · Credibility Theory. Izgūts 2026-06-18 no https://scholargate.app/lv/compare