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Do-Validation for Kernel Density Estimation

Author

Listed:
  • Mammen, Enno
  • Martínez Miranda, María Dolores
  • Nielsen, Jens Perch
  • Sperlich, Stefan

Abstract

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Suggested Citation

  • Mammen, Enno & Martínez Miranda, María Dolores & Nielsen, Jens Perch & Sperlich, Stefan, 2011. "Do-Validation for Kernel Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 651-660.
    • Handle: RePEc:bes:jnlasa:v:106:i:494:y:2011:p:651-660
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    Citations

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    Cited by:

    1. Karim M Abadir & Michel Lubrano, 2024. "Explicit solutions for the asymptotically optimal bandwidth in cross-validation," Post-Print hal-04678541, HAL.
    2. Max Köhler & Anja Schindler & Stefan Sperlich, 2014. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," International Statistical Review, International Statistical Institute, vol. 82(2), pages 243-274, August.
    3. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    4. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    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. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    7. Olga Y. Savchuk, 2020. "One-sided cross-validation for nonsmooth density functions," Computational Statistics, Springer, vol. 35(3), pages 1253-1272, September.
    8. María Luz Gámiz & Enno Mammen & María Dolores Martínez Miranda & Jens Perch Nielsen, 2016. "Double one-sided cross-validation of local linear hazards," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 755-779, September.
    9. repec:grz:wpaper:2012-10 is not listed on IDEAS
    10. Gámiz Pérez, M. Luz & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2013. "Smoothing survival densities in practice," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 368-382.
    11. M. Hiabu & E. Mammen & M. D. Martìnez-Miranda & J. P. Nielsen, 2016. "In-sample forecasting with local linear survival densities," Biometrika, Biometrika Trust, vol. 103(4), pages 843-859.
    12. Gámiz, María Luz & Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch, 2022. "Missing link survival analysis with applications to available pandemic data," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    13. Michael Govorov & Giedrė Beconytė & Gennady Gienko, 2023. "Trivariate Kernel Density Estimation of Spatiotemporal Crime Events with Case Study for Lithuania," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    14. Olga Y. Savchuk & Jeffrey D. Hart, 2017. "Fully robust one-sided cross-validation for regression functions," Computational Statistics, Springer, vol. 32(3), pages 1003-1025, September.

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