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Optimal bandwidth selection in kernel density estimation for continuous time dependent processes

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  • El Heda, Khadijetou
  • Louani, Djamal

Abstract

The choice of the smoothing parameter in nonparametric function estimation is of major concern. The estimation accuracy highly depends on how such a choice is performed. In this paper, we construct a bandwidth selection procedure pertaining to the kernel density estimation when a continuous time dependent and stationary process is considered.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:stapro:v:138:y:2018:i:c:p:9-19
    DOI: 10.1016/j.spl.2018.02.001
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    References listed on IDEAS

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    1. José E. Chacón & Carlos Tenreiro, 2012. "Exact and Asymptotically Optimal Bandwidths for Kernel Estimation of Density Functionals," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 523-548, September.
    2. Didi, Sultana & Louani, Djamal, 2013. "Consistency results for the kernel density estimate on continuous time stationary and dependent data," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1262-1270.
    3. 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.
    4. C. Tenreiro, 2017. "A weighted least-squares cross-validation bandwidth selector for kernel density estimation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(7), pages 3438-3458, April.
    5. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
    6. É. Youndjé & P. Sarda & P. Vieu, 1996. "Optimal smooth hazard estimates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(2), pages 379-394, December.
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    Cited by:

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    3. Chaouch, Mohamed & Laïb, Naâmane, 2019. "Optimal asymptotic MSE of kernel regression estimate for continuous time processes with missing at random response," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
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