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Robust scale estimation in the error‐components model using the empirical characteristic function
Author(s) -
Markatou Marianthi,
Horowitz Joel L.
Publication year - 1995
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315381
Subject(s) - estimator , robustness (evolution) , affine transformation , monte carlo method , mathematics , influence function , equivariant map , scale (ratio) , function (biology) , m estimator , computer science , statistics , biochemistry , chemistry , physics , quantum mechanics , evolutionary biology , biology , pure mathematics , gene
Robust estimators of the scale parameters in the error‐components model are described. The new estimators are based on the empirical characteristic functions of appropriate sets of residuals and are affine equivariant, consistent and asymptotically normal. The robustness of the new estimators is investigated via influence‐function calculations. The results of Monte Carlo experiments and an example based on real data illustrate the usefulness of the estimators.