Wavelet density estimation for mixing and size-biased data.

Published in: Journal of inequalities and applications (2018)

This paper considers wavelet estimation for a multivariate density function based on mixing and size-biased data. We provide upper bounds for the mean integrated squared error (MISE) of wavelet estimators. It turns out that our results reduce to the corresponding theorem of Shirazi and Doosti (Stat. Methodol. 27:12-19, 2015), when the random sample is independent.

Keyphrases

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