RT Journal Article
T1 Robust median estimator in logistic regression
A1 Hobza, Pavel
A1 Pardo Llorente, Leandro
A1 Vajda, Igor
AB This paper introduces a median estimator of the logistic regression parameters. It is defined as the classical L-1-estimator applied to continuous data Z(1),..., Z(n) obtained by a statistical smoothing of the original binary logistic regression observations Y-1,..., Y-n. Consistency and asymptotic normality of this estimator are proved. A method called enhancement is introduced which in some cases increases the efficiency of this estimator. Sensitivity to contaminations and leverage points is studied by simulations and compared in this manner with the sensitivity of some robust estimators previously introduced to the logistic regression. The new estimator appears to be more robust for larger sample sizes and higher levels of contamination.
PB Elsevier Science Bv
SN 0378-3758
YR 2008
FD 2008-12-01
LK https://hdl.handle.net/20.500.14352/50246
UL https://hdl.handle.net/20.500.14352/50246
LA eng
DS Docta Complutense
RD 21 abr 2025