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Tao Wang

4 papers hereh-index 13553 citations33 works total

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

author position
  • first author2
  • middle author2

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

fields
  • math.ST2
  • stat.ME2
same name
  • Tao Wang — 41 papers, h 21
  • Tao Wang — 31 papers, h 52
  • Tao Wang — 30 papers, h 10
  • Tao Wang — 19 papers, h 8
  • Tao Wang — 19 papers, h 18
  • Tao Wang — 18 papers, h 14

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
20142017
most citedVariable selection and estimation for semi-parametric multiple-index models

11 citations · 21 across the 4 of their papers we have counts for

collaborators

4 papers

stat.ME2017★ 1 cited

Counting Process Based Dimension Reduction Methods for Censored Outcomes

Qiang Sun, Ruoqing Zhu, Tao Wang +1

We propose a class of dimension reduction methods for right censored survival data using a counting process representation of the failure process. Semiparametric estimating equatio…

math.ST2016★ 9 cited

Dimensionality determination: a thresholding double ridge ratio criterion

Xuehu Zhu, Tao Wang, Lixing Zhu

Popularly used eigendecomposition-based criteria such as BIC type, ratio estimation and principal component-based criterion often underdetermine model dimensionality for regression…

math.ST2015★ 11 cited

Variable selection and estimation for semi-parametric multiple-index models

Tao Wang, Peirong Xu, Lixing Zhu

In this paper, we propose a novel method to select significant variables and estimate the corresponding coefficients in multiple-index models with a group structure. All existing a…

stat.ME2014

Transformed sufficient dimension reduction

Tao Wang, Xu Guo, Peirong Xu +1

A novel general framework is proposed in this paper for dimension reduction in regression to fill the gap between linear and fully nonlinear dimension reduction. The main idea is t…

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