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The Weight Function in the Bounded Influence Regression Quantile Estimator for the AR(1) Model with Additive Outliers
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 Title & Authors
The Weight Function in the Bounded Influence Regression Quantile Estimator for the AR(1) Model with Additive Outliers
Jung Byoung Cheol; Han Sang Moon;
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 Abstract
In this study, we investigate the effects of the weight function in the bounded influence regression quantile (BIRQ) estimator for the AR(l) model with additive outliers. In order to down-weight the outliers of X -axis, the Mallows` (1973) weight function has been commonly used in the BIRQ estimator. However, in our Monte Carlo study, the BIRQ estimator using the Tukey`s bisquare weight function shows less MSE and bias than that of using the Mallows` weight function or Huber`s weight function. Thus, the use of the Tukey`s weight function is recommended in the BIRQ estimator for our model.
 Keywords
Weight Function;AR(1);Regression quantile estimator;
 Language
Korean
 Cited by
 References
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