research
∙
08/02/2023
A Simple Bootstrap for Chatterjee's Rank Correlation
We prove that an m out of n bootstrap procedure for Chatterjee's rank co...
share
research
∙
06/29/2023
Efficient subsampling for exponential family models
We propose a novel two-stage subsampling algorithm based on optimal desi...
research
∙
06/15/2023
A CLT for the difference of eigenvalue statistics of sample covariance matrices
In the case where the dimension of the data grows at the same rate as th...
research
∙
05/15/2023
Testing equivalence of multinomial distributions – a constrained bootstrap approach
In this paper we develop a novel bootstrap test for the comparison of tw...
research
∙
03/28/2023
A reinforced learning approach to optimal design under model uncertainty
Optimal designs are usually model-dependent and likely to be sub-optimal...
research
∙
02/03/2023
Towards active learning: A stopping criterion for the sequential sampling of grain boundary degrees of freedom
Many materials processes and properties depend on the anisotropy of the ...
research
∙
02/02/2023
Comparing regression curves – an L^1-point of view
In this paper we compare two regression curves by measuring their differ...
research
∙
01/11/2023
Testing separability for continuous functional data
Analyzing the covariance structure of data is a fundamental task of stat...
research
∙
11/01/2022
Fluctuations of the diagonal entries of a large sample precision matrix
For a given p× n data matrix X_n with i.i.d. centered entries and a popu...
research
∙
10/31/2022
Independence testing in high dimensions
This paper takes a different look on the problem of testing the mutual i...
research
∙
08/22/2022
Quantifying deviations from structural assumptions in the analysis of nonstationary function-valued processes: a general framework
We present a general theory to quantify the uncertainty from imposing st...
research
∙
05/04/2022
Validating Approximate Slope Homogeneity in Large Panels
Statistical inference for large data panels is omnipresent in modern eco...
research
∙
03/09/2022
Detecting relevant changes in the spatiotemporal mean function
For a spatiotemporal process {X_j(s,t) |  s ∈ S , t ∈ T }_j =1, … , n, w...
research
∙
02/16/2022
An RKHS approach for pivotal inference in functional linear regression
We develop methodology for testing hypotheses regarding the slope functi...
research
∙
01/10/2022
Rearranged dependence measures
Most of the popular dependence measures for two random variables X and Y...
research
∙
12/14/2021
The integrated copula spectrum
Frequency domain methods form a ubiquitous part of the statistical toolb...
research
∙
11/26/2021
Efficient prediction of grain boundary energies from atomistic simulations via sequential design
Data based materials science is the new promise to accelerate materials ...
research
∙
10/15/2021
Multivariate Mean Comparison under Differential Privacy
The comparison of multivariate population means is a central task of sta...
research
∙
09/28/2021
Statistical inference for function-on-function linear regression
Function-on-function linear regression is important for understanding th...
research
∙
09/20/2021
Similarity of competing risks models with constant intensities in an application to clinical healthcare pathways involving prostate cancer surgery
The recent availability of routine medical data, especially in a univers...
research
∙
09/08/2021
Confidence surfaces for the mean of locally stationary functional time series
The problem of constructing a simultaneous confidence band for the mean ...
research
∙
08/21/2021
Statistical Quantification of Differential Privacy: A Local Approach
In this work we introduce a new approach for statistical quantification ...
research
∙
08/16/2021
Statistical inference for the slope parameter in functional linear regression
In this paper we consider the linear regression model Y =S X+ε with func...
research
∙
07/21/2021
Linear spectral statistics of sequential sample covariance matrices
Independent p-dimensional vectors with independent complex or real value...
research
∙
04/19/2021
Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes
For the class of Gauss-Markov processes we study the problem of asymptot...
research
∙
03/18/2021
Nonparametric and high-dimensional functional graphical models
We consider the problem of constructing nonparametric undirected graphic...
research
∙
01/28/2021
Reproducing kernel Hilbert spaces, polynomials and the classical moment problems
We show that polynomials do not belong to the reproducing kernel Hilbert...
research
∙
01/14/2021
Optimal designs for comparing regression curves – dependence within and between groups
We consider the problem of designing experiments for the comparison of t...
research
∙
09/18/2020
A note on optimal designs for estimating the slope of a polynomial regression
In this note we consider the optimal design problem for estimating the s...
research
∙
09/15/2020
A Portmanteau-type test for detecting serial correlation in locally stationary functional time series
The Portmanteau test provides the vanilla method for detecting serial co...
research
∙
06/12/2020
Detecting relevant differences in the covariance operators of functional time series – a sup-norm approach
In this paper we propose statistical inference tools for the covariance ...
research
∙
05/31/2020
Sequential change point detection in high dimensional time series
Change point detection in high dimensional data has found considerable i...
research
∙
05/22/2020
A distribution free test for changes in the trend function of locally stationary processes
In the common time series model X_i,n = μ (i/n) + ε_i,n with non-station...
research
∙
04/26/2020
Efficient tests for bio-equivalence in functional data
We study the problem of testing the equivalence of functional parameters...
research
∙
04/09/2020
Pivotal tests for relevant differences in the second order dynamics of functional time series
Motivated by the need to statistically quantify differences between mode...
research
∙
03/26/2020
Quantifying deviations from separability in space-time functional processes
The estimation of covariance operators of spatio-temporal data is in man...
research
∙
03/20/2020
Design admissibility and de la Garza phenomenon in multi-factor experiments
The determination of an optimal design for a given regression problem is...
research
∙
03/12/2020
Statistical Inference for High Dimensional Panel Functional Time Series
In this paper we develop statistical inference tools for high dimensiona...
research
∙
02/21/2020
Efficient model-based Bioequivalence Testing
The classical approach to analyze pharmacokinetic (PK) data in bioequiva...
research
∙
02/14/2020
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators
Classical change point analysis aims at (1) detecting abrupt changes in ...
research
∙
01/02/2020
Prediction in locally stationary time series
We develop an estimator for the high-dimensional covariance matrix of a ...
research
∙
11/18/2019
Detecting structural breaks in eigensystems of functional time series
Detecting structural changes in functional data is a prominent topic in ...
research
∙
10/19/2019
Equivalence tests for binary efficacy-toxicity responses
Clinical trials often aim to compare a new drug with a reference treatme...
research
∙
09/13/2019
Two-sample tests for relevant differences in the eigenfunctions of covariance operators
This paper deals with two-sample tests for functional time series data, ...
research
∙
08/12/2019
Identifying shifts between two regression curves
This article studies the problem whether two convex (concave) regression...
research
∙
08/12/2019
Prediction in regression models with continuous observations
We consider the problem of predicting values of a random process or fiel...
research
∙
06/19/2019
Optimal designs for estimating individual coefficients in polynomial regression with no intercept
In a seminal paper studden1968 characterized c-optimal designs in regres...
research
∙
06/03/2019
A new approach for open-end sequential change point monitoring
We propose a new sequential monitoring scheme for changes in the paramet...
research
∙
05/24/2019
Likelihood ratio tests for many groups in high dimensions
In this paper we investigate the asymptotic distribution of likelihood r...
research
∙
04/02/2019
