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Haixiang Zhang

5 papers hereh-index 11615 citations31 works total

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

author position
  • sole author1
  • first author2
  • middle author1
  • last author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • stat.ME4
  • stat.CO1
same name
  • Haixiang Zhang — 16 papers, h 1
  • Haixiang Zhang — 7 papers, h 24
  • Haixiang Zhang — 3 papers, h 2
  • Haixiang Zhang — 3 papers, h 4
  • Haixiang Zhang — 2 papers, h 4
  • Haixiang Zhang — 1 paper, h 1

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
20222026
most citedApproximating Partial Likelihood Estimators via Optimal Subsampling

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing stat.MEShow all

4 papers · 1 filter

stat.ME2026

Efficient Poisson Subsampling for the Partially Linear Additive Cox Model

Dongxiao Han, Liuquan Sun, Chunjie Wang +3

To address the computational and storage challenges often encountered in large-scale survival data analysis, we propose an efficient Poisson subsampling method for the partially li…

stat.ME2023

Efficient Adjusted Joint Significance Test and Sobel-Type Confidence Interval for Mediation Effect

Haixiang Zhang

Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the…

stat.ME2022

Renewable Learning for Multiplicative Regression with Streaming Datasets

Tianzhen Wang, Haixiang Zhang, Liuquan Sun

When large amounts of data continuously arrive in streams, online updating is an effective way to reduce storage and computational burden. The key idea of online updating is that t…

stat.ME2022★ 1 cited

Approximating Partial Likelihood Estimators via Optimal Subsampling

Haixiang Zhang, Lulu Zuo, HaiYing Wang +1

With the growing availability of large-scale biomedical data, it is often time-consuming or infeasible to directly perform traditional statistical analysis with relatively limited…

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