Full Bayesian wavelet inference with a nonparametric prior |
| |
Authors: | Xue Wang Stephen G Walker |
| |
Institution: | University of Kent at Canterbury, Canterbury, UK |
| |
Abstract: | In this paper, we introduce a new Bayesian nonparametric model for estimating an unknown function in the presence of Gaussian noise. The proposed model involves a mixture of a point mass and an arbitrary (nonparametric) symmetric and unimodal distribution for modeling wavelet coefficients. Posterior simulation uses slice sampling ideas and the consistency under the proposed model is discussed. In particular, the method is shown to be computationally competitive with some of best Empirical wavelet estimation methods. |
| |
Keywords: | Stick-breaking priors Slice sampling Wavelet shrinkage Consistency |
本文献已被 ScienceDirect 等数据库收录! |