3 citations · 6 across the 8 of their papers we have counts for
8 papers
Identification problem and quasi-maximum likelihood estimation for matrix-variate CP-factor models
Hanzi Ye, Chun Yip Yau
Matrix-valued time series, arising in diverse fields such as economics, neuroscience, and recommender systems, have become increasingly prominent in modern data analysis. Among var…
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…
Predicting Future Change-points in Time Series
Chak Fung Choi, Chunxue Li, Chun Yip Yau +1
Change-point detection and estimation procedures have been widely developed in the literature. However, commonly used approaches in change-point analysis have mainly been focusing…
Functional Autoregressive Processes in Reproducing Kernel Hilbert Spaces
Daren Wang, Zifeng Zhao, Rebecca Willett +1
We study the estimation and prediction of functional autoregressive~(FAR) processes, a statistical tool for modeling functional time series data. Due to the infinite-dimensional na…
Asymptotic Spectral Theory for Spatial Data
Wai Leong Ng, Chun Yip Yau
In this paper we study the asymptotic theory for spectral analysis of stationary random fields, including linear and nonlinear fields. Asymptotic properties of Fourier coefficients…
Alternating Pruned Dynamic Programming for Multiple Epidemic Change-Point Estimation
Zifeng Zhao, Chun Yip Yau
In this paper, we study the problem of multiple change-point detection for a univariate sequence under the epidemic setting, where the behavior of the sequence alternates between a…
A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Processes
Zifeng Zhao, Ting Fung Ma, Wai Leong Ng +1
This paper develops a unified and computationally efficient method for change-point estimation along the time dimension in a non-stationary spatio-temporal process. By modeling a n…
Inference for Multiple Change-points in Linear and Non-linear Time Series Models
Wai Leong Ng, Shenyi Pan, Chun Yip Yau
In this paper we develop a generalized likelihood ratio scan method (GLRSM) for multiple change-points inference in piecewise stationary time series, which estimates the number and…