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Sankhya B

, Volume 80, Issue 2, pp 341–368 | Cite as

Data-Driven Bandwidth Selection for Recursive Kernel Density Estimators Under Double Truncation

  • Yousri Slaoui
Article
  • 10 Downloads

Abstract

In this paper we proposed a data-driven bandwidth selection procedure of the recursive kernel density estimators under double truncation. We showed that, using the selected bandwidth and a special stepsize, the proposed recursive estimators outperform the nonrecursive one in terms of estimation error in many situations. We corroborated these theoretical results through simulation study. The proposed estimators are then applied to data on the luminosity of quasars in astronomy. We corroborated these theoretical results through simulation study, then, we applied the proposed estimators to data on the luminosity of quasars in astronomy.

Keywords and phrases

Density estimation Stochastic approximation algorithm Smoothing Curve fitting Double truncated data. 

AMS (2000) subject classification

Primary 62G07, 62L20 Secondary 65D10, 62N01 

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Notes

Acknowledgements

We are grateful to referee and an Editor for their helpful comments, which have led to this substantially improved version of the paper.

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Copyright information

© Indian Statistical Institute 2018

Authors and Affiliations

  1. 1.Laboratoire de Mathématiques et ApplicationUniversité de PoitiersFuturoscope ChasseneuilFrance

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