首页 | 本学科首页   官方微博 | 高级检索  
     检索      


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!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号