91 citations · 170 across the 6 of their papers we have counts for
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Asymptotic equivalence for inference on the volatility from noisy observations
Markus Reiß
We consider discrete-time observations of a continuous martingale under measurement error. This serves as a fundamental model for high-frequency data in finance, where an efficient…
Asymptotic Equivalence for Nonparametric Regression with Non-Regular Errors
Alexander Meister, Markus Reiß
Asymptotic equivalence in Le Cam's sense for nonparametric regression experiments is extended to the case of non-regular error densities, which have jump discontinuities at their e…
Pointwise adaptive estimation for robust and quantile regression
Markus Reiss, Yves Rozenholc, Charles-Andre Cuenod
A nonparametric procedure for robust regression estimation and for quantile regression is proposed which is completely data-driven and adapts locally to the regularity of the regre…
Nonlinear estimation for linear inverse problems with error in the operator
Marc Hoffmann, Markus Reiss
We study two nonlinear methods for statistical linear inverse problems when the operator is not known. The two constructions combine Galerkin regularization and wavelet thresholdin…
Nonparametric estimation for Lévy processes from low-frequency observations
Michael H. Neumann, Markus Reiss
We suppose that a Lévy process is observed at discrete time points. A rather general construction of minimum-distance estimators is shown to give consistent estimators of the Lévy-…
Asymptotic equivalence for nonparametric regression with multivariate and random design
Markus Reiß
We show that nonparametric regression is asymptotically equivalent in Le Cam's sense with a sequence of Gaussian white noise experiments as the number of observations tends to infi…