Robustness analysis of a maximum correntropy framework for linear regression
Copyright policy )Robustness analysis of a maximum correntropy framework for linear regression
In this paper we formulate a solution of the robust linear regression problem in a general framework of correntropy maximization. Our formulation yields a unified class of estimators which includes the Gaussian and Laplacian kernel-based correntropy estimators as special cases. An analysis of the robustness properties is then provided. The analysis includes a quantitative characterization of the informativity degree of the regression which is appropriate for studying the stability of the estimator. Using this tool, a sufficient condition is expressed under which the parametric estimation error is shown to be bounded. Explicit expression of the bound is given and discussion on its numerical computation is supplied. For illustration purpose, two special cases are numerically studied.
10 pages, 5 figures, To appear in Automatica
Estimation and detection in stochastic control theory, Identification in stochastic control theory, Linear regression; mixed models, maximum correntropy, outliers, robust estimation, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 510, [SPI.AUTO] Engineering Sciences [physics]/Automatic, FOS: Electrical engineering, electronic engineering, information engineering, Sensitivity (robustness), system identification
Estimation and detection in stochastic control theory, Identification in stochastic control theory, Linear regression; mixed models, maximum correntropy, outliers, robust estimation, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 510, [SPI.AUTO] Engineering Sciences [physics]/Automatic, FOS: Electrical engineering, electronic engineering, information engineering, Sensitivity (robustness), system identification
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!