The Bayesian Wavelet Thresholding Estimators of Nonparametric Regression Model Based on Mixture Prior Distribution
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Mahmood Afshari , Abouzar Bazyari * , Yeganeh Moradian , Hamid Karamikabir |
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Abstract: (4172 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. |
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Keywords: Bayes Factor, Mixture Prior Distribution, Nonparametric Regression Function, Wavelet Thresholding Estimator. |
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Full-Text [PDF 855 kb]
(1254 Downloads)
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Type of Study: Research |
Subject:
Statistical Inference Received: 2019/02/18 | Accepted: 2020/04/2 | Published: 2021/02/28
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