RT Generic
T1 Shrinkage reweighted regression
A1 Cabana Garceran del Vall, Elisa
A1 Lillo Rodríguez, Rosa Elvira
A1 Laniado Rodas, Henry
A2 Universidad Carlos III de Madrid. Departamento de Estadística, 
AB 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 times, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socio-economic 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.
SN 2387-0303
YR 2019
FD 2019-06
LK https://hdl.handle.net/10016/28500
UL https://hdl.handle.net/10016/28500
LA eng
NO This research was partially supported by MINISTERIO DE ECONOMIA,INDUSTRIA Y COMPETITIVIDAD, award number: ECO2015-66593-P.
DS e-Archivo
RD 27 jul. 2024