Article ID Journal Published Year Pages File Type
1146382 Journal of Multivariate Analysis 2011 19 Pages PDF
Abstract

We propose a new robust estimator of the regression coefficients in a linear regression model. The proposed estimator is the only robust estimator based on integration rather than optimization. It allows for dependence between errors and regressors, is n-consistent, and asymptotically normal. Moreover, it has the best achievable breakdown point of regression invariant estimators, has bounded gross error sensitivity, is both affine invariant and regression invariant  , and the number of operations required for its computation is linear in nn. An extension would result in bounded local shift sensitivity, also.

Related Topics
Physical Sciences and Engineering Mathematics Numerical Analysis
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