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Kernel density estimation for linear processes: asymptotic normality and bandwidth selection

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  • Marc Hallin
  • Lanh T. Tran

Abstract

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Suggested Citation

  • Marc Hallin & Lanh T. Tran, 1996. "Kernel density estimation for linear processes: asymptotic normality and bandwidth selection," ULB Institutional Repository 2013/2055, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:ulb:ulbeco:2013/2055
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    Cited by:

    1. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2015. "Estimators in step regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 124-129.
    2. Tang Qingguo & Cheng Longsheng, 2010. "B-spline estimation for spatial data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 197-217.
    3. Toshio Honda, 2009. "Nonparametric density estimation for linear processes with infinite variance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 413-439, June.
    4. Zudi Lu, 2001. "Asymptotic Normality of Kernel Density Estimators under Dependence," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(3), pages 447-468, September.
    5. Dimitris N. Politis & Peter F. Tarassenko & Vyacheslav A. Vasiliev, 2022. "Estimating Smoothness and Optimal Bandwidth for Probability Density Functions," Stats, MDPI, vol. 6(1), pages 1-20, December.
    6. Hwang, Eunju & Shin, Dong Wan, 2012. "Stationary bootstrap for kernel density estimators under ψ-weak dependence," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1581-1593.
    7. Schick, Anton & Wefelmeyer, Wolfgang, 2006. "Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes," Statistics & Probability Letters, Elsevier, vol. 76(16), pages 1756-1760, October.

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