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researcher

Jun Li

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author2
  • first author1
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ME4
same name
  • Jun Li — 30 papers, h 27
  • Jun Li — 28 papers
  • Jun Li — 26 papers, h 51
  • Jun Li — 15 papers
  • Jun Li — 13 papers, h 19
  • Jun Li — 9 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedChange Point Detection in the Mean of High-Dimensional Time Series Data under Dependence

6 citations · 6 across the 3 of their papers we have counts for

collaborators
Showing stat.MEShow all

4 papers · 1 filter

stat.ME2022

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…

stat.ME2021

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…

stat.ME2019

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…

stat.ME2019★ 6 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.