On Jackknifing Kernel Regression Function Estimators.
NORTH CAROLINA UNIV AT CHAPEL HILL INST OF STATISTICS
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Estimation of the value of a regression function at a point of continuity using a kernal-type estimator is discussed and improvements of the technique by a generalized jackknife estimator are presented. It is shown that the generalized jackknife technique produces estimators with faster bias rates. In a small example it is investigated, if the generalized jackknife method works for all choices of bandwidths. It turns out that an improper choice of this parameter may inflate the mean square error of the generalized jackknife estimator. Author
- Statistics and Probability