頁籤選單縮合
題 名 | Wavelet Shrinkage for Correlated Data and Inverse Problems: Adaptivity Results |
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作 者 | Johnstone,Iain M.; | 書刊名 | Statistica Sinica |
卷 期 | 9:1 1999.01[民88.01] |
頁 次 | 頁51-83 |
分類號 | 319 |
關鍵詞 | Adaptation; Correlated data; Fractional brownian motion; Linear inverse problems; Long range dependence; Mixing conditions; Oracle inequalities; Rates of convergence; Unbiased risk estimate; Wavelet vaguelette decomposition; Wavelet shrinkage; Wavelet thresholding; |
語 文 | 英文(English) |
英文摘要 | Johnstone and Silverman (1997) described a level-dependent thresholding method for extracting signals from correlated noise. The thresholds were chosen to minimize a data based unbiased risk criterion. Here we show that in certain asymptotic models encompassing short and long range dependence, these methods are simultaneously asymptotically minimax up to constants over a broad range of Besov classes. We indicate the extension of the methods and results to a class of linear inverse problems possessing a wavelet vaguelette decomposition. |
本系統中英文摘要資訊取自各篇刊載內容。