96 citations · 331 across the 16 of their papers we have counts for
14 papers · 1 filter
Central limit theorems for high dimensional dependent data
Jinyuan Chang, Xiaohui Chen, Mingcong Wu
Motivated by statistical inference problems in high-dimensional time series data analysis, we first derive non-asymptotic error bounds for Gaussian approximations of sums of high-d…
Maximum likelihood estimation of potential energy in interacting particle systems from single-trajectory data
Xiaohui Chen
This paper concerns the parameter estimation problem for the quadratic potential energy in interacting particle systems from continuous-time and single-trajectory data. Even though…
Stratified incomplete local simplex tests for curvature of nonparametric multiple regression
Yanglei Song, Xiaohui Chen, Kengo Kato
Principled nonparametric tests for regression curvature in are often statistically and computationally challenging. This paper introduces the stratified incomplete…
Estimation of dynamic networks for high-dimensional nonstationary time series
Mengyu Xu, Xiaohui Chen, Wei Biao Wu
This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural break…
A robust bootstrap change point test for high-dimensional location parameter
Mengjia Yu, Xiaohui Chen
We consider the problem of change point detection for high-dimensional distributions in a location family when the dimension can be much larger than the sample size. In change poin…
Approximating high-dimensional infinite-order -statistics: statistical and computational guarantees
Yanglei Song, Xiaohui Chen, Kengo Kato
We study the problem of distributional approximations to high-dimensional non-degenerate -statistics with random kernels of diverging orders. Infinite-order -statistics (IOUS…
Randomized incomplete -statistics in high dimensions
Xiaohui Chen, Kengo Kato
This paper studies inference for the mean vector of a high-dimensional -statistic. In the era of Big Data, the dimension of the -statistic and the sample size of the…
Finite sample change point inference and identification for high-dimensional mean vectors
Mengjia Yu, Xiaohui Chen
Cumulative sum (CUSUM) statistics are widely used in the change point inference and identification. For the problem of testing for existence of a change point in an independent sam…
Jackknife multiplier bootstrap: finite sample approximations to the -process supremum with applications
Xiaohui Chen, Kengo Kato
This paper is concerned with finite sample approximations to the supremum of a non-degenerate -process of a general order indexed by a function class. We are primarily intereste…
Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications
Xiaohui Chen
This paper studies the Gaussian and bootstrap approximations for the probabilities of a non-degenerate U-statistic belonging to the hyperrectangles in when the dimen…
Sparse transition matrix estimation for high-dimensional and locally stationary vector autoregressive models
Xin Ding, Ziyi Qiu, Xiaohui Chen
We consider the estimation of the transition matrix in the high-dimensional time-varying vector autoregression (TV-VAR) models. Our model builds on a general class of locally stati…
Gaussian approximation for the sup-norm of high-dimensional matrix-variate U-statistics and its applications
Xiaohui Chen
This paper studies the Gaussian approximation of high-dimensional and non-degenerate U-statistics of order two under the supremum norm. We propose a two-step Gaussian approximation…
Regularized estimation of linear functionals of precision matrices for high-dimensional time series
Xiaohui Chen, Mengyu Xu, Wei Biao Wu
This paper studies a Dantzig-selector type regularized estimator for linear functionals of high-dimensional linear processes. Explicit rates of convergence of the proposed estimato…
Covariance and precision matrix estimation for high-dimensional time series
Xiaohui Chen, Mengyu Xu, Wei Biao Wu
We consider estimation of covariance matrices and their inverses (a.k.a. precision matrices) for high-dimensional stationary and locally stationary time series. In the latter case…