Applying robust regression to insurance

DOI10.1016/0167-6687(84)90020-9zbMath0523.62082OpenAlexW2050092676MaRDI QIDQ1056505

Peter J. Rousseeuw, A. Leroy, B. Daniels

Publication date: 1984

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6687(84)90020-9

zbMATH Keywords

outliersrobust regressionlife insurancehealth insuranceleast trimmed squarespension funds

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to actuarial sciences and financial mathematics (62P05) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (6)

Bayesian nonparametric regression models for modeling and predicting healthcare claims ⋮ Bayesian quantile regression model for claim count data ⋮ Neural networks approach for determining total claim amounts in insurance ⋮ Using quantile regression for rate-making ⋮ Robust regression credibility: The influence function approach ⋮ A note on the breakdown point of the least median of squares and least trimmed squares estimators

Cites Work

• Robust regression using repeated medians
• A General Qualitative Definition of Robustness
• Unnamed Item

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