5 papers · 1 filter
CP-factorization for high dimensional tensor time series and double projection iterations
Jinyuan Chang, Guanglin Huang, Qiwei Yao +1
We adopt the canonical polyadic (CP) decomposition to model high-dimensional tensor time series. Our primary goal is to identify and estimate the factor loadings in the CP decompos…
Testing independence and conditional independence in high dimensions via coordinatewise Gaussianization
Jinyuan Chang, Yue Du, Jing He +1
We propose new statistical tests, in high-dimensional settings, for testing the independence of two random vectors and their conditional independence given a third random vector. T…
Spatio-Temporal Autoregressions for High Dimensional Matrix-Valued Time Series
Baojun Dou, Jing He, Sudhir Tiwari +1
Motivated by predicting intraday trading volume curves, we consider two spatio-temporal autoregressive models for matrix time series, in which each column may represent daily tradi…
Identification and estimation for matrix time series CP-factor models
Jinyuan Chang, Yue Du, Guanglin Huang +1
We propose a new method for identifying and estimating the CP-factor models for matrix time series. Unlike the generalized eigenanalysis-based method of Chang et al. (2023) for whi…
On the modelling and prediction of high-dimensional functional time series
Jinyuan Chang, Qin Fang, Xinghao Qiao +1
We propose a two-step procedure to model and predict high-dimensional functional time series, where the number of function-valued time series is large in relation to the length…