A New Kernel Distribution Function Estimator Based on a Non-parametric Transformation of the Data |
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Authors: | JAN W H SWANEPOEL FRANCOIS C VAN GRAAN |
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Institution: | Department of Statistics, North-West University |
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Abstract: | Abstract. A new kernel distribution function (df) estimator based on a non-parametric transformation of the data is proposed. It is shown that the asymptotic bias and mean squared error of the estimator are considerably smaller than that of the standard kernel df estimator. For the practical implementation of the new estimator a data-based choice of the bandwidth is proposed. Two possible areas of application are the non-parametric smoothed bootstrap and survival analysis. In the latter case new estimators for the survival function and the mean residual life function are derived. |
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Keywords: | bias kernel distribution function estimator mean squared error non-parametric transformation smoothed bootstrap survival analysis |
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