頁籤選單縮合
題 名 | Asymptotic Minimaxity of Wavelet Estimators with Sampled Data |
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作 者 | Donoho,David L.; Johnstone,Iain M.; | 書刊名 | Statistica Sinica |
卷 期 | 9:1 1999.01[民88.01] |
頁 次 | 頁1-32 |
分類號 | 319.52 |
關鍵詞 | Besov spaces; Bounded operators between besov spaces; Minimax estimation; Thresholding; Wavelet transforms of sampled data; Wavelets; White noise equivalence; |
語 文 | 英文(English) |
英文摘要 | Donoho and Johnstone (1998) studied a setting where data were obtained in the continuum white noise model and showed that scalar nonlinearities applied to wavelet coefficients gave estimators which were asymptotically minimax over Besov balls. They claimed that this implied similar asymptotic minimiaxity results in the sampled-data model. In this paper we carefully develop and fully prove this implication. Our results are based on a careful definition of an empirical wavelet transform and precise bounds on the discrepancy between empirical wavelet coefficients and the theoretical wavelet coefficients. |
本系統中英文摘要資訊取自各篇刊載內容。