47 citations · 66 across the 6 of their papers we have counts for
6 papers
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…
Uniform convergence of convolution estimators for the response density in nonparametric regression
Anton Schick, Wolfgang Wefelmeyer
We consider a nonparametric regression model with a random covariate that is independent of the error . Then the density of the response i…
Optimality of estimators for misspecified semi-Markov models
Ursula U. Müller, Anton Schick, Wolfgang Wefelmeyer
Suppose we observe a geometrically ergodic semi-Markov process and have a parametric model for the transition distribution of the embedded Markov chain, for the conditional distrib…
Uniformly root- consistent density estimators for weakly dependent invertible linear processes
Anton Schick, Wolfgang Wefelmeyer
Convergence rates of kernel density estimators for stationary time series are well studied. For invertible linear processes, we construct a new density estimator that converges, in…
Efficient prediction for linear and nonlinear autoregressive models
Ursula U. Müller, Anton Schick, Wolfgang Wefelmeyer
Conditional expectations given past observations in stationary time series are usually estimated directly by kernel estimators, or by plugging in kernel estimators for transition d…
Estimating invariant laws of linear processes by U-statistics
Anton Schick, Wolfgang Wefelmeyer
Suppose we observe an invertible linear process with independent mean-zero innovations and with coefficients depending on a finite-dimensional parameter, and we want to estimate th…