Year: 2025
Type: article
Abstract: This paper investigates nonparametric estimations of a density function within a mixed density model. A linear wavelet density estimator and an adaptive nonlinear wavelet estimator are proposed using wavelet method and hard thresholding algorithm. Under some mild conditions, the convergence rates over the mean integrated squared error of two wavelet density estimators are proved. Compared with the optimal convergence rates of nonparametric wavelet estimations, those two wavelet estimators all are optimal in some cases. Finally, the performances of two wavelet estimators are verified by numerical experimental studies.
Source: Axioms
Authors: Dan Liang, Junke Kou
Institution: Guilin University of Electronic Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G379561779, G5262786094, G8318044250
OpenAlex ID: W4414623413