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:: Volume 14, Issue 1 (8-2020) ::
JSS 2020, 14(1): 195-214 Back to browse issues page
Wavelet-Based Quantile Density Estimation By Block Thresholding Method Under L2 Loss Function
Esmaeil Shirazi *
Abstract:   (2874 Views)
In this paper, we consider an adaptive wavelet estimation for quantile density function based on block thresholding method and obtain it's convergence rate under L2 loss function over Besove function spaces. This work is an extension of results in Chesneau et. al. (2016) and shows that the block threshold estimator gets better convergence rate (Optimal) than the estimators proposed by Chesneau et. al. (2016). The performance of the proposed estimator is investigated with a simulation study.
Keywords: Adaptive Estimation, Quantile Density Function, Block Thresholding Method, Besov Function Space, Wavelets.
Full-Text [PDF 1269 kb]   (1112 Downloads)    
Type of Study: Research | Subject: Applied Statistics
Received: 2018/08/1 | Accepted: 2019/10/3 | Published: 2020/02/20
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Shirazi E. Wavelet-Based Quantile Density Estimation By Block Thresholding Method Under L2 Loss Function. JSS 2020; 14 (1) :195-214
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 1 (8-2020) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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