18 citations · 34 across the 8 of their papers we have counts for
8 papers
Finite Sample t-Tests for High-Dimensional Means
Jun Li
Size distortion can occur if an asymptotic testing procedure requiring diverging sample sizes, is implemented to data with very small sample sizes. In this paper, we consider one-s…
Max-Type and Sum-Type Procedures for Online Change-Point Detection in the Mean of High-Dimensional Data
Jun Li
We propose two procedures to detect a change in the mean of high-dimensional online data. One is based on a max-type U-statistic and another is based on a sum-type U-statistic. The…
Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks
Lingjun Li, Jun Li
In this paper, we develop an online change-point detection procedure in the covariance structure of high-dimensional data. A new stopping rule is proposed to terminate the process…
Change Point Detection in the Mean of High-Dimensional Time Series Data under Dependence
Jun Li, Minya Xu, Ping-Shou Zhong +1
High-dimensional time series are characterized by a large number of measurements and complex dependence, and often involve abrupt change points. We propose a new procedure to detec…
A Neighborhood-Assisted Hotelling's Test for High-Dimensional Means
Jun Li, Yumou Qiu, Lingjun Li
Many tests have been proposed to remedy the classical Hotelling's test in the "large , small " paradigm, but the existence of an optimal sum-of-squares type test has no…
Test for Temporal Homogeneity of Means in High-dimensional Longitudinal Data
Ping-Shou Zhong, Jun Li
This paper considers the problem of testing temporal homogeneity of -dimensional population mean vectors from the repeated measurements of subjects over times. To cope w…