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A Study on Bandwidth Selection in Density Estimation under Dependence

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  • Kim, Tae Yoon
  • Cox, Denis D.

Abstract

Hart and Vieu proposed a modified cross validation (MCV), the "leave-(2l+1)-out" version of the simple cross validation for bandwidth selection under dependence and established its asymptotic optimality for a certain class ofl. In this article, we investigate the convergence rates of MCV.

Suggested Citation

  • Kim, Tae Yoon & Cox, Denis D., 1997. "A Study on Bandwidth Selection in Density Estimation under Dependence," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 190-203, August.
    • Handle: RePEc:eee:jmvana:v:62:y:1997:i:2:p:190-203
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    References listed on IDEAS

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    1. Kim, Tae Yoon, 1993. "A note on moment bounds for strong mixing sequences," Statistics & Probability Letters, Elsevier, vol. 16(2), pages 163-168, January.
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    Cited by:

    1. Barbeito, Inés & Cao, Ricardo, 2016. "Smoothed stationary bootstrap bandwidth selection for density estimation with dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 130-147.
    2. El Heda, Khadijetou & Louani, Djamal, 2018. "Optimal bandwidth selection in kernel density estimation for continuous time dependent processes," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 9-19.
    3. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.
    4. Estévez-Pérez, Graciela, 2002. "On convergence rates for quadratic errors in kernel hazard estimation," Statistics & Probability Letters, Elsevier, vol. 57(3), pages 231-241, April.
    5. M. Sköld, 2001. "The Asymptotic Variance of the Continuous-Time Kernel Estimator with Applications to Bandwidth Selection," Statistical Inference for Stochastic Processes, Springer, vol. 4(1), pages 99-117, January.

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