We prove that an m out of n bootstrap procedure for Chatterjee's rank
co...
We propose a novel two-stage subsampling algorithm based on optimal desi...
In the case where the dimension of the data grows at the same rate as th...
In this paper we develop a novel bootstrap test for the comparison of tw...
Optimal designs are usually model-dependent and likely to be sub-optimal...
Many materials processes and properties depend on the anisotropy of the
...
In this paper we compare two regression curves by measuring their differ...
Analyzing the covariance structure of data is a fundamental task of
stat...
For a given p× n data matrix X_n with i.i.d. centered
entries and a popu...
This paper takes a different look on the problem of testing the mutual
i...
We present a general theory to quantify the uncertainty from imposing
st...
Statistical inference for large data panels is omnipresent in modern eco...
For a spatiotemporal process {X_j(s,t) | s ∈ S , t ∈ T }_j =1,
… , n, w...
We develop methodology for testing hypotheses regarding the slope functi...
Most of the popular dependence measures for two random variables X and Y...
Frequency domain methods form a ubiquitous part of the statistical toolb...
Data based materials science is the new promise to accelerate materials
...
The comparison of multivariate population means is a central task of
sta...
Function-on-function linear regression is important for understanding th...
The recent availability of routine medical data, especially in a
univers...
The problem of constructing a simultaneous confidence band for the mean
...
In this work we introduce a new approach for statistical quantification ...
In this paper we consider the linear regression model Y =S X+ε
with func...
Independent p-dimensional vectors with independent complex or real value...
For the class of Gauss-Markov processes we study the problem of asymptot...
We consider the problem of constructing nonparametric undirected graphic...
We show that polynomials do not belong to the reproducing kernel Hilbert...
We consider the problem of designing experiments for the comparison of t...
In this note we consider the optimal design problem for estimating the s...
The Portmanteau test provides the vanilla method for detecting serial
co...
In this paper we propose statistical inference tools for the covariance
...
Change point detection in high dimensional data has found considerable
i...
In the common time series model X_i,n = μ (i/n) + ε_i,n
with non-station...
We study the problem of testing the equivalence of functional parameters...
Motivated by the need to statistically quantify differences between mode...
The estimation of covariance operators of spatio-temporal data is in man...
The determination of an optimal design for a given regression problem is...
In this paper we develop statistical inference tools for high dimensiona...
The classical approach to analyze pharmacokinetic (PK) data in bioequiva...
Classical change point analysis aims at (1) detecting abrupt changes in ...
We develop an estimator for the high-dimensional covariance matrix of a
...
Detecting structural changes in functional data is a prominent topic in
...
Clinical trials often aim to compare a new drug with a reference treatme...
This paper deals with two-sample tests for functional time series data, ...
This article studies the problem whether two convex (concave) regression...
We consider the problem of predicting values of a random process or fiel...
In a seminal paper studden1968 characterized c-optimal designs in
regres...
We propose a new sequential monitoring scheme for changes in the paramet...
In this paper we investigate the asymptotic distribution of likelihood r...
In this paper we construct optimal designs for frequentist model averagi...