# Dating the Break in High-dimensional Data

@article{Wang2020DatingTB, title={Dating the Break in High-dimensional Data}, author={Runmin Wang and Xiaofeng Shao}, journal={arXiv: Methodology}, year={2020} }

This paper is concerned with estimation and inference for the location of a change point in the mean of independent high-dimensional data. Our change point location estimator maximizes a new U-statistic based objective function, and its convergence rate and asymptotic distribution after suitable centering and normalization are obtained under mild assumptions. Our estimator turns out to have better efficiency as compared to the least squares based counterpart in the literature. Based on the…

## 7 Citations

### Adaptive Change Point Monitoring for High-Dimensional Data

- 2022

Computer Science, Mathematics

This paper develops recursive algorithms to improve the computational efficiency of the monitoring procedure and introduces a class of estimators for $q$-norm of the covariance matrix and proves their ratio consistency.

### Inference on the Change Point in High Dimensional Dynamic Graphical Models

- 2020

Computer Science, Mathematics

It is shown that the proposed estimator retains sufficient adaptivity against plugin estimates of the edge structure of the underlying graphical models, in order to yield an O(\psi^{-2}) rate of convergence of the change point estimator in the integer scale.

### Segmentation of high dimensional means over multi-dimensional change points and connections to regression trees

- 2021

Mathematics, Computer Science

This article is motivated by the objective of providing a new analytically tractable and fully frequentist framework to characterize and implement regression trees while also allowing a multivariate…

### Sequential change point detection in high dimensional time series

- 2022

Computer Science, Mathematics

Electronic Journal of Statistics

In a high dimensional scenario it is shown that the new monitoring schemes have asymptotic level alpha under the null hypothesis of no change and are consistent under the alternative of a change in at least one component.

### Inference on the change point under a high dimensional sparse mean shift

- 2021

Mathematics

We study a plug in least squares estimator for the change point parameter where change is in the mean of a high dimensional random vector under subgaussian or subexponential distributions. We obtain…

### Optimal multiple change-point detection for high-dimensional data

- 2023

Computer Science

Electronic Journal of Statistics

This manuscript provides a generic algorithm for aggregating local homogeneity tests into an estimator of change-points in a time series and establishes that the error rates of the collection of test directly translate into detection properties of the change-point estimator.

### Monitoring Network Changes in Social Media

- 2021

Computer Science

SSRN Electronic Journal

A method and the corresponding algorithm for monitoring changes in dynamic networks to feature the complexity of networks and strong theoretical guarantees on both the false alarm rate and detection delays are derived in a sub-Gaussian setting.

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