7 papers
Transferring supremum-norm rates and weak convergence of covariance kernel estimators to functional principal components
Hajo Holzmann, Kevin Wilk
We show that -perturbation theory can be used to transfer rates of convergence in the supremum norm as well as weak convergence in the space of continuous functions from covar…
Evaluating HWE and Association in Genome Wide Association Studies: A Unified Procedure
Stefan Böhringer, Hajo Holzmann
In genome wide association studies (GWASs) based on a case-control design, single nucleotide polymorphisms (SNPs) are typically evaluated for an association test and a Hardy-Weinbe…
Beyond average warming: Two-sample inference for dense-sparse functional data reveals changes in intraday temperature patterns
Kevin Wilk, Hajo Holzmann
Modern weather stations in Germany record daily temperatures every 10 minutes, whereas measurements from historical reference periods are often only available at much coarser tempo…
Optimal rates for estimating the covariance kernel from synchronously sampled functional data
Max Berger, Hajo Holzmann
We obtain minimax-optimal convergence rates in the supremum norm, including information-theoretic lower bounds, for estimating the covariance kernel of a stochastic process which i…
Smooth and rough paths in mean derivative estimation for functional data
Max Berger, Hajo Holzmann
In this paper, in a multivariate setting we derive near optimal rates of convergence in the minimax sense for estimating partial derivatives of the mean function for functional dat…
Multivariate root-n-consistent smoothing parameter free matching estimators and estimators of inverse density weighted expectations
Hajo Holzmann, Alexander Meister
Expected values weighted by the inverse of a multivariate density or, equivalently, Lebesgue integrals of regression functions with multivariate regressors occur in various areas o…