Wavelet based estimation of the derivatives of a density for a negatively associated process

Yogendra P. Chaubey, Hassan Doosti, B. L. S. Prakasa Rao

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15 Citations (Scopus)

Abstract

Here we adopt the method of estimation for the derivatives of a probability density function based on wavelets discussed in Prakasa Rao (1996) to the case of negatively associated random variables. An upper bound on Lp-loss for the resulting estimator is given which extends such a result for the integrated mean square error (IMSE) given in Prakasa Rao (1996). Also, considering the case of derivative of order zero, the results given by Kerkyacharian and Picard (1992), Tribouley (1995) and Leblanc (1996) are obtained as special cases.

Original languageEnglish
Pages (from-to)453-463
Number of pages11
JournalJournal of Statistical Theory and Practice
Volume2
Issue number3
DOIs
Publication statusPublished - 2008
Externally publishedYes

Keywords

  • Besov space
  • multiresolution analysis
  • negative dependence
  • nonparametric estimation
  • wavelets

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