Adaptive Wavelet Estimation of a Biased Density for Strongly Mixing Sequences | Zendy

Christophe Chesneau | Zendy

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Adaptive Wavelet Estimation of a Biased Density for Strongly Mixing Sequences

Author(s) -

Christophe Chesneau

Publication year - 2011

Publication title -

international journal of mathematics and mathematical sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.21

H-Index - 39

eISSN - 1687-0425

pISSN - 0161-1712

DOI - 10.1155/2011/604150

Subject(s) - mathematics , estimator , mixing (physics) , wavelet , density estimation , upper and lower bounds , mean squared error , thresholding , class (philosophy) , exponential growth , adaptive estimator , statistics , mathematical analysis , artificial intelligence , computer science , physics , quantum mechanics , image (mathematics)

The estimation of a biased density for exponentially stronglymixing sequences is investigated. We construct a new adaptive waveletestimator based on a hard thresholding rule. We determine a sharpupper bound of the associated mean integrated square error for a wideclass of functions

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