Abstract:The hat matrix is an important auxiliary quantity in linear regression theory for detecting errors in predictors. Traditionally, the comparison of the diagonal elements with a calibration point serves as decision rule for separating a dominant linear population from outliers. However, several problems exist : first, the calibration point is not well defined because no exact statistical distribution (asymptotic form) of the hat matrix diagonal exists [1]. Secondly, being based on the standard covariance matrix,… Show more
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