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math.ST2018
Estimating the error distribution function in nonparametric regression
Ursula U. Müller, Anton Schick, Wolfgang Wefelmeyer
We construct an efficient estimator for the error distribution function of the nonparametric regression model Y = r(Z) + e. Our estimator is a kernel smoothed empirical distributio…
math.ST2013★ 24 cited
The transfer principle: A tool for complete case analysis
Hira L. Koul, Ursula U. Müller, Anton Schick
This paper gives a general method for deriving limiting distributions of complete case statistics for missing data models from corresponding results for the model where all data ar…
math.ST2009★ 39 cited
Estimating linear functionals in nonlinear regression with responses missing at random
Ursula U. Müller
We consider regression models with parametric (linear or nonlinear) regression function and allow responses to be ``missing at random.'' We assume that the errors have mean zero an…