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This study extends ‘empirical transformation’ in kernel smoothing to conditional probability density and regression function estimations. We propose nonparametric conditional probability density and r...egression function estimators, which are based on an extension of ´Cwik and Mielniczuk (1989)’s method. We derived asymptotic properties of the proposed estimators and conducted a simulation that showed mean squared errors of conditional probability density and regression function estimators.show more
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