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Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data
Published 27 Oct 2016 in stat.ME | (1610.08768v1)
Abstract: A residual-based empirical distribution function is proposed to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and this estimator is shown to be asymptotically most precise.
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