Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data
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Date
2016
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Abstract
We propose a residual-based empirical distribution function to estimate the distribution function
of the errors of a heteroskedastic nonparametric regression with responses missing at random based on
completely observed data, and we show this estimator is asymptotically most precise.
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Keywords
heteroskedastic, empirical distribution function, efficient estimator, transfer principle, local polynomial smoother, nonparametric regression