Nonparametric covariance model

There has been considerable attention paid to estimation of conditional variance functions in the literature. We propose a nonparametric model for the conditional covariance matrix. A kernel estimator is developed, its asymptotic bias and variance are derived, and its asymptotic normality is established. A data example is used to illustrate the proposed procedure.

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Work Title Nonparametric covariance model
Access
Open Access
Creators
  1. Jianxin Yin
  2. Zhi Geng
  3. Runze Li
  4. Hansheng Wang
Keyword
  1. Conditional variance
  2. Heteroscedasticity
  3. Kernel regression
  4. Nonparametric covariance model
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Statistica Sinica
Publication Date 2010
Related URLs
Deposited July 19, 2022

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Version 1
published

  • Created
  • Added A20n120.pdf
  • Added Creator Jianxin Yin
  • Added Creator Zhi Geng
  • Added Creator Runze Li
  • Added Creator Hansheng Wang
  • Published
  • Updated Keyword, Related URLs, Publication Date Show Changes
    Keyword
    • Conditional variance, Heteroscedasticity, Kernel regression, Nonparametric covariance model
    Related URLs
    • https://pubmed.ncbi.nlm.nih.gov/21170152
    Publication Date
    • 2010-01-01
    • 2010
  • Updated