14 papers
Mean estimation in spatial functional data
Holger Dette, Qirui Hu
Functional mean estimation exhibits a sparse-to-dense phase transition as the number of measurements per curve increases. For spatially indexed functional data, however, dependence…
Model Specification Test for Stationary Functional Time Series
Yan Cui, Holger Dette, Zhou Zhou
We develop a general framework for model specification testing in stationary functional time series. The approach is based on an autoregressive approximation that represents a broa…
Self-normalization for Spectral Density Integrals
Holger Dette, Sebastian Kühnert
Integrals of spectral densities are frequently used to summarize spectral characteristics of linear processes. This work studies self-normalization for estimators of such integrals…
Testing for correct model specification in copula regression models
Holger Dette, Philip Dörr
We propose a goodness-of-fit test for semiparametric copula regression models. Such models express the regression function in terms of marginal distribution functions and copula de…
A spectral based coefficient of determination for the fit of an MA(q) model
Holger Dette, Sebastian Kühnert
We develop a spectral based coefficient of determination to measure how well the spectral density of a stationary linear process is represented by the class of MA() models. Usin…
Kernel Estimation Of Chatterjee's Dependence Coefficient
Mona Azadkia, Holger Dette
A dependence coefficient suggested by Chatterjee (2021) has attracted considerable attention in recent years. It takes values between 0 and 1, vanishes if and only if the correspon…
Inference for Multiple Change-points in Piecewise Locally Stationary Time Series
Wai Leong Ng, Xinyi Tang, Mun Lau Cheung +3
Change-point detection and locally stationary time series modeling are two major approaches for the analysis of non-stationary data. The former aims to identify stationary phases b…
Convergence of covariance and spectral density estimates for high-dimensional functional time series
Bufan Li, Xinghao Qiao, Weichi Wu +1
Second-order characteristics including covariance and spectral density functions are fundamentally important for both statistical applications and theoretical analysis in functiona…
Measuring deviations from spherical symmetry
Lujia Bai, Holger Dette
Most of the work on checking spherical symmetry assumptions on the distribution of the -dimensional random vector has its focus on statistical tests for the null hypothesis…
Practically significant change points in high dimension -- measuring signal strength pro active component
Pascal Quanz, Holger Dette
We consider the change point testing problem for high-dimensional time series. Unlike conventional approaches, where one tests whether the difference of the mean vectors before…
Pivotal inference for linear predictions in stationary processes
Holger Dette, Sebastian Kühnert
In this paper we develop pivotal inference for the final (FPE) and relative final prediction error (RFPE) of linear forecasts in stationary processes. Our approach is based on a se…
A portmanteau test for multivariate non-stationary functional time series with an increasing number of lags
Lujia Bai, Holger Dette, Weichi Wu
Multivariate locally stationary functional time series provide a flexible framework for modeling functional data exhibiting both temporal and spatial dependencies while allowing fo…
On the lack of weak continuity of Chatterjee's correlation coefficient
Axel Bücher, Holger Dette
Chatterjee's correlation coefficient has recently been proposed as a new association measure for bivariate random vectors that satisfies a number of desirable properties. Among the…
Exponential Inequalities for Some Mixing Processes and Dynamic Systems
Zihao Yuan, Holger Dette
Many important dynamic systems, time series models or even algorithms exhibit non-strong mixing properties. In this paper, we introduce the general concept of $\mathcal{C}_{p,\math…