[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 14, Issue 2 (2-2021) ::
J. of Stat. Sci. 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:   (1113 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]   (113 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2019/02/18 | Accepted: 2020/04/2 | Published: 2021/02/28
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Afshari M, Bazyari A, Moradian Y, Karamikabir H. The Bayesian Wavelet Thresholding Estimators of Nonparametric Regression Model Based on Mixture Prior Distribution. J. of Stat. Sci.. 2021; 14 (2) :287-306
URL: http://jss.irstat.ir/article-1-648-en.html


Volume 14, Issue 2 (2-2021) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
Persian site map - English site map - Created in 0.05 seconds with 29 queries by YEKTAWEB 4256