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THEORETICAL PROPERTIES OF ROBUST ESTIMATORS
Defining a Robust Procedure
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allocation of leverage amount of leverage Andrews asymptotic variance Bisquare Biweight breakdown point BSUB collinearity column space condition number corresponding data matrix data sets dependent variable diagonal elements distribution F DOUBLE PRECISION error distributions estimators of location Figure Gastwirth Gaussian gross—error—sensitivity Hampel high leverage point Householder reflection Huber increases influence curve influence function least squares analysis least squares fit least squares procedure least squares regression leverage and residual leverage equal linear local—shift—sensitivity long—tailed M—estimator major axis mean squared error median minor axis multicollinearity normal distribution one-step orthogonal orthogonal matrix outliers outperform percent plots principal component vectors PROGRAM pseudovariance qualitatively robust redescending M-estimators residual error robust algorithms robust estimators robust location estimators robust regression algorithms robust scale robust statistics sample mean scale estimator sensitivity curve singular values slope Statistics Stigler swindle symmetric distribution trimmed mean Tukey underlying distribution weighted least squares weighting function Welsch Winsorized mean zero