ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Teori Kebolehpercayaan×Sistem Bonus-Malus×
BidangSains AktuariSains Aktuari
KeluargaRegression modelRegression model
Tahun asal19671995
PengasasHans BühlmannJean Lemaire
JenisWeighted linear blend of individual and collective experienceActuarial experience-rating model
Sumber perintisBühlmann, H. (1967). Experience rating and credibility. ASTIN Bulletin, 4(3), 199–207. DOI ↗Lemaire, J. (1995). Bonus-Malus Systems in Automobile Insurance. Kluwer Academic Publishers. ISBN: 978-0-7923-9545-5
AliasBühlmann Credibility, Experience Rating, Linear Credibility Estimator, Güvenilirlik TeorisiNo-Claim Discount System, Merit Rating System, Experience Rating in Automobile Insurance, Prim-Ceza Sistemi
Berkaitan32
RingkasanCredibility 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.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.
ScholarGateSet data
  1. v1
  2. 1 Sumber
  3. PUBLISHED
  1. v1
  2. 1 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Credibility Theory · Bonus-Malus System. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare