Optimal convergence rates of wavelet estimators for a hidden density in a mixture model
Abstract
This paper investigates nonparametric estimations of a density function in a mixture model. Firstly, a lower bound estimation under \( ????^{p}(1 ≤ ???? < +\infty ) error of an arbitrary density estimator is discussed. Secondly, a linear estimator and an adaptive nonlinear estimator of the unknown density function are constructed by the wavelet method.The rates of convergence of those two wavelet estimators are discussed with some mild conditions. Combining with the lower bound estimations, two wavelet estimators can attain the optimal convergen
Fields of Study & Subjects
Statistical Methods and Inference
Bayesian Methods and Mixture Models
Statistical Methods and Bayesian Inference
Publication details
- Journal / source
- Mathematical communications
- Publisher
- School of Applied Mathematics and Informatics
- Volume
- 31
- Issue
- 1
- Pages
- 83–113
- Publication date
- 2 April 2026
- Language
- EN