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Nonparametric Kernel Distribution Function Estimation with kerdiest: An R Package for Bandwidth Choice and Applications

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  • Quintela-del-Río, Alejandro
  • Estévez-Pérez, Graciela

Abstract

The R package kerdiest has been designed for computing kernel estimators of the distribution function and other related functions. Because of its usefulness in real applications, the bandwidth parameter selection problem has been considered, and a cross-validation method and two of plug-in type have been implemented. Moreover, three relevant functions in nature hazards have also been programmed. The package is completed with two interesting data sets, one of geological type (a complete catalogue of the earthquakes occurring in the northwest of the Iberian Peninsula) and another containing the maximum peak flow levels of a river in the United States of America.

Suggested Citation

  • Quintela-del-Río, Alejandro & Estévez-Pérez, Graciela, 2012. "Nonparametric Kernel Distribution Function Estimation with kerdiest: An R Package for Bandwidth Choice and Applications," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i08).
    • Handle: RePEc:jss:jstsof:v:050:i08
    DOI: http://hdl.handle.net/10.18637/jss.v050.i08
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    Cited by:

    1. D. Blanke & D. Bosq, 2018. "Polygonal smoothing of the empirical distribution function," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 263-287, July.
    2. Eftekharian, A. & Razmkhah, M., 2017. "On estimating the distribution function and odds using ranked set sampling," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 1-10.
    3. Helena Ferreira & Ana Paula Martins & Maria Graça Temido, 2021. "Extremal behaviour of a periodically controlled sequence with imputed values," Statistical Papers, Springer, vol. 62(6), pages 2991-3013, December.

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