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極値理論 (EVT)×損失分布モデル×
分野ファイナンス保険数理学
系統Regression modelRegression model
提唱年20012012
提唱者Coles (textbook treatment); McNeil, Frey & EmbrechtsKlugman, Panjer & Willmot
種類Tail / extreme-event modelParametric probability model
原典Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598Klugman, S. A., Panjer, H. H., & Willmot, G. E. (2012). Loss Models: From Data to Decisions (4th ed.). Wiley. ISBN: 978-1-118-31532-3
別名EVT, generalized extreme value, generalized Pareto distribution, peaks over thresholdSeverity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı Modeli
関連53
概要Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold.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手法を比較: Extreme Value Theory · Loss Distribution Model. 2026-06-20に以下より取得 https://scholargate.app/ja/compare