108 citations · 268 across the 9 of their papers we have counts for
11 papers
High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization
Wanrong Zhu, Zhipeng Lou, Ziyang Wei +1
Uncertainty quantification for estimation through stochastic optimization solutions in an online setting has gained popularity recently. This paper introduces a novel inference met…
Estimation of Grouped Time-Varying Network Vector Autoregression Models
Degui Li, Bin Peng, Songqiao Tang +1
This paper introduces a flexible time-varying network vector autoregressive model framework for large-scale time series. A latent group structure is imposed on the heterogeneous an…
Sharp connections between Berry-Esseen characteristics and Edgeworth expansions for stationary processes
Moritz Jirak, Wei Biao Wu, Ou Zhao
Given a weakly dependent stationary process, we describe the transition between a Berry-Esseen bound and a second order Edgeworth expansion in terms of the Berry-Esseen characteris…
Probability inequalities for high dimensional time series under a triangular array framework
Fang Han, Weibiao Wu
Study of time series data often involves measuring the strength of temporal dependence, on which statistical properties like consistency and central limit theorem are built. Histor…
Simultaneous Inference for High Dimensional Mean Vectors
Zhipeng Lou, Wei Biao Wu
Let be i.i.d. random vectors. We aim to perform simultaneous inference for the mean vector with finite polynomial moments and a…
Towards a general theory for non-linear locally stationary processes
Rainer Dahlhaus, Stefan Richter, Wei Biao Wu
In this paper some general theory is presented for locally stationary processes based on the stationary approximation and the stationary derivative. Laws of large numbers, central…
A Dual Field-of-View Zoom Metalens
Guoxing Zheng, Weibiao Wu, Zile Li +4
Conventional optical zoom system is bulky, expensive and complicated for real time adjustment. Recent progress in the metasurface research has provided a new solution to achieve in…
Self-normalized Cramér Type Moderate Deviations under Dependence
Xiaohong Chen, Qi-Man Shao, Wei Biao Wu
We establish a Cramér-type moderate deviation result for self-normalized sums of weakly dependent random variables, where the moment requirement is much weaker than the non-self-no…
A central limit theorem for stationary random fields
Mohamed El Machkouri, Dalibor Volny, Wei Biao Wu
This paper establishes a central limit theorem and an invariance principle for a wide class of stationary random fields under natural and easily verifiable conditions. More precise…
Central limit theorem for Fourier transforms of stationary processes
Magda Peligrad, Wei Biao Wu
We consider asymptotic behavior of Fourier transforms of stationary ergodic sequences with finite second moments. We establish a central limit theorem (CLT) for almost all frequenc…
Local linear quantile estimation for nonstationary time series
Zhou Zhou, Wei Biao Wu
We consider estimation of quantile curves for a general class of nonstationary processes. Consistency and central limit results are obtained for local linear quantile estimates und…