Multiwavelet density estimation for biased data

Abstract In this article, we present our method for multiwavelet estimation for a density function based on random samples from a weighted distribution. First, we propose linear and nonlinear multiwavelet estimators for the biased data. Then, we provide and prove the upper bound of risk for the proposed nonlinear estimator over a large class of densities in the Besov space, . Finally, we provide simulation and real data experiments to illustrate the effectiveness and behavior of the proposed method and estimator.

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