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Jia Chen

4 papers hereh-index 15923 citations45 works total

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

author position
  • first author3
  • middle author1

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

fields
  • math.ST2
  • econ.EM1
  • stat.ME1
same name
  • Jia Chen — 12 papers, h 8
  • Jia Chen — 11 papers, h 9
  • Jia Chen — 11 papers, h 2
  • Jia Chen — 8 papers, h 3
  • Jia Chen — 7 papers, h 4
  • Jia Chen — 5 papers, h 20

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
20122023
most citedEstimation in semi-parametric regression with non-stationary regressors

42 citations · 83 across the 4 of their papers we have counts for

collaborators

4 papers

econ.EM2023★ 1 cited

Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure

Xiaorong Yang, Jia Chen, Degui Li +1

This paper considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large p…

stat.ME2023★ 2 cited

Estimating Time-Varying Networks for High-Dimensional Time Series

Jia Chen, Degui Li, Yuning Li +1

We explore time-varying networks for high-dimensional locally stationary time series, using the large VAR model framework with both the transition and (error) precision matrices ev…

math.ST2015★ 38 cited

Semiparametric GEE analysis in partially linear single-index models for longitudinal data

Jia Chen, Degui Li, Hua Liang +1

In this article, we study a partially linear single-index model for longitudinal data under a general framework which includes both the sparse and dense longitudinal data cases. A…

math.ST2012★ 42 cited

Estimation in semi-parametric regression with non-stationary regressors

Jia Chen, Jiti Gao, Degui Li

In this paper, we consider a partially linear model of the form Yt​=Xtτ​θ0​+g(Vt​)+εt​, t=1,...,n, where {Vt​} is a β null recurrent Markov chain, {Xt​} is a sequenc…

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