1 citations · 1 across the 4 of their papers we have counts for
5 papers
An adaptive -type test for high-dimensional white noise
Jinyuan Chang, Jing He, Weiming Li +1
We propose a new -type test for white noise which allows the dimension of the time series to either (i) be a fixed constant, or (ii) diverge with the sample size . The…
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…
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…
HDTSA: An R package for high-dimensional time series analysis
Jinyuan Chang, Jing He, Chen Lin +1
High-dimensional time series analysis has become increasingly important in fields such as finance, economics, and biology. The two primary tasks for high-dimensional time series an…
Statistical inferences for complex dependence of multimodal imaging data
Jinyuan Chang, Jing He, Jian Kang +1
Statistical analysis of multimodal imaging data is a challenging task, since the data involves high-dimensionality, strong spatial correlations and complex data structures. In this…