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Bootstrap Inference×广义最小二乘法 (GLS)×损失分布模型×
领域统计学统计学精算学
方法族Regression modelRegression modelRegression model
起源年份197919352012
提出者Bradley EfronAlexander Craig AitkenKlugman, Panjer & Willmot
类型Resampling-based inferenceLinear estimatorParametric probability model
开创性文献Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. 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 ↗Klugman, S. A., Panjer, H. H., & Willmot, G. E. (2012). Loss Models: From Data to Decisions (4th ed.). Wiley. ISBN: 978-1-118-31532-3
别名bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap ÇıkarımıGLS, Aitken estimator, EGLS, feasible GLSSeverity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı Modeli
相关533
摘要Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.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.A Loss Distribution Model is a parametric statistical framework used in actuarial science to characterise the probabilistic behaviour of insurance claim amounts and frequencies. Developed comprehensively by Klugman, Panjer, and Willmot in their foundational text Loss Models: From Data to Decisions (first edition 1998, fourth edition 2012), these models underpin premium rating, reserving, reinsurance pricing, and regulatory capital calculations across the insurance and risk-management industries.
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ScholarGate方法对比: Bootstrap Inference · Generalized Least Squares · Loss Distribution Model. 于 2026-06-19 检索自 https://scholargate.app/zh/compare