Details

Autor(en) / Beteiligte

• Cabana, Elisa
• Lillo, Rosa E.
• Laniado, Henry

Titel

Robust regression based on shrinkage with application to Living Environment Deprivation

Ist Teil von

• Stochastic environmental research and risk assessment, 2020-02, Vol.34 (2), p.293-310

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2020

Quelle

Springer LINK 全文期刊数据库

Beschreibungen/Notizen

• A robust estimator is proposed for the parameters that characterize the linear regression problem. It is based on the notion of shrinkages, often used in Finance and previously studied for outlier detection in multivariate data. A thorough simulation study is conducted to investigate: the efficiency with Normal and heavy-tailed errors, the robustness under contamination, the computational time, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socioeconomic data-set about the Living Environment Deprivation of areas in Liverpool (UK), are studied. The results from the simulations and the real data examples show the advantages of the proposed robust estimator in regression.