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:: Volume 14, Issue 2 (2-2021) ::
JSS 2021, 14(2): 287-306 Back to browse issues page
The Bayesian Wavelet Thresholding Estimators of Nonparametric Regression Model Based on Mixture Prior Distribution
Mahmood Afshari , Abouzar Bazyari * , Yeganeh Moradian , Hamid Karamikabir
Abstract:   (4114 Views)
In this paper, the wavelet estimators of the nonparametric regression function based on the various thresholds under the mixture prior distribution and the mean square error loss function in Bosove space are computed. Also, using a simulation study the optimality of different wavelet thresholding estimators such as posterior mean, posterior median, Bayes factor, universal threshold and sure threshold are investigated. The results show that the average mean square error of sure threshold estimator is less than the other obtained estimators. 
Keywords: Bayes Factor, Mixture Prior Distribution, Nonparametric Regression Function, Wavelet Thresholding Estimator.
Full-Text [PDF 855 kb]   (1218 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2019/02/18 | Accepted: 2020/04/2 | Published: 2021/02/28
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Afshari M, Bazyari A, Moradian Y, Karamikabir H. The Bayesian Wavelet Thresholding Estimators of Nonparametric Regression Model Based on Mixture Prior Distribution. JSS 2021; 14 (2) :287-306
URL: http://jss.irstat.ir/article-1-648-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 2 (2-2021) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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