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K. Zhu

10 papers hereh-index 16740 citations62 works total

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

author position
  • sole author1
  • first author1
  • middle author3
  • last author5

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • econ.EM4
  • stat.ME4
  • math.ST2
same name
  • K. Zhu — 230 papers, h 54
  • K. Zhu — 55 papers, h 32
  • K. Zhu — 24 papers, h 21
  • K. Zhu — 22 papers, h 28
  • K. Zhu — 10 papers, h 12
  • K. Zhu — 9 papers, h 22

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
20152020
most citedConfidence intervals for parameters in high-dimensional sparse vector autoregression

2 citations · 5 across the 6 of their papers we have counts for

collaborators
Showing stat.MEShow all

4 papers · 1 filter

stat.ME2020★ 2 cited

Confidence intervals for parameters in high-dimensional sparse vector autoregression

Ke Zhu, Hanzhong Liu

Vector autoregression (VAR) models are widely used to analyze the interrelationship between multiple variables over time. Estimation and inference for the transition matrices of VA…

stat.ME2019

Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model

Feiyu Jiang, Dong Li, Ke Zhu

This paper considers a semiparametric generalized autoregressive conditional heteroskedasticity (S-GARCH) model. For this model, we first estimate the time-varying long run compone…

stat.ME2018

New HSIC-based tests for independence between two stationary multivariate time series

Guochang Wang, Wai Keung Li, Ke Zhu

This paper proposes some novel one-sided omnibus tests for independence between two multivariate stationary time series. These new tests apply the Hilbert-Schmidt independence crit…

stat.ME2018

Statistical inference for autoregressive models under heteroscedasticity of unknown form

Ke Zhu

This paper provides an entire inference procedure for the autoregressive model under (conditional) heteroscedasticity of unknown form with a finite variance. We first establish the…

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