Asymptotically efficient estimators for nonparametric heteroscedastic regression models

Details Asymptotically efficient estimators for nonparametric heteroscedastic regression models Asymptotically efficient estimators for nonparametric heteroscedastic regression models

2007-11-29

arxiv.org/abs/0711.4725v1

Mathematics

Statistics Theory

Scientific paper

This paper concerns the estimation of the regression function at a given
point in nonparametric heteroscedastic models with Gaussian noise or with noise
having unknown distribution. In the two cases an asymptotically efficient
kernel estimator is constructed for the minimax absolute error risk.

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