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مدل مک برای ذخیره‌سازی خسارات با روش نردبان زنجیره‌ای×حداقل مربعات تعمیم‌یافته (GLS)×
حوزهعلوم اکچوئریآمار
خانوادهRegression modelRegression model
سال پیدایش19931935
پدیدآورThomas MackAlexander Craig Aitken
نوعStochastic loss reserving modelLinear estimator
منبع بنیادینMack, T. (1993). Distribution-free calculation of the standard error of chain ladder reserve estimates. ASTIN Bulletin, 23(2), 213–225. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
نام‌های دیگرDevelopment Factor Method, Link Ratio Method, Loss Development Method, Zincir Merdiven YöntemiGLS, Aitken estimator, EGLS, feasible GLS
مرتبط33
خلاصهChain-Ladder Reserving is a stochastic actuarial method for estimating outstanding claim liabilities from a run-off triangle of cumulative paid losses. Formalized by Thomas Mack in 1993, it provides distribution-free estimates of reserve amounts along with their standard errors, making it a cornerstone of property-casualty insurance reserving and regulatory practice worldwide.Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
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ScholarGateمقایسهٔ روش‌ها: Chain-Ladder Reserving · Generalized Least Squares. بازیابی‌شده در 2026-06-19 از https://scholargate.app/fa/compare