Restenosis
发表于 2025-3-28 15:28:21
Bayesian Approach to Wavelet Decomposition and Shrinkageel for its wavelet coefficients by establishing a relationship between the hyperparameters of the proposed model and the parameters of those Besov spaces within which realizations from the prior will fall. Such a relation may be seen as giving insight into the meaning of the Besov space parameters t
讨厌
发表于 2025-3-28 22:17:15
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FLING
发表于 2025-3-28 22:53:41
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Isthmus
发表于 2025-3-29 03:21:32
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Facilities
发表于 2025-3-29 07:55:48
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Geyser
发表于 2025-3-29 11:38:43
Minimax Restoration and Deconvolution we study linear and non-linear diagonal estimators in an orthogonal basis. General conditions are given to build nearly minimax optimal estimators with a thresholding in an orthogonal basis. The deconvolution of bounded variation signals is studied in further details, with an application to the deb
insipid
发表于 2025-3-29 16:53:54
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玷污
发表于 2025-3-29 20:19:01
Best Basis Representations with Prior Statistical Modelssignal. Applying these deterministic search techniques to stochastic signals may, however, lead to statistically unreliable results. In this chapter, we revisit this problem and introduce prior models on the underlying signal in noise. We propose several techniques to derive the prior parameters and
微不足道
发表于 2025-3-30 01:17:02
Modeling Dependence in the Wavelet Domainrecursive way to compute the within- and across-level covari-ances. We then show the usefulness of those findings in some of the best known applications of wavelets in statistics. Wavelet shrinkage attempts to estimate a function from noisy data. When approaching the problem from a Bayesian point of
推崇
发表于 2025-3-30 05:29:49
MCMC Methods in Wavelet Shrinkage: Non-Equally Spaced Regression, Density and Spectral Density Estimity estimation. The common theme in all three applications is the lack of posterior independence for the wavelet coefficients ... In contrast, most commonly considered applications of wavelet decompositions in Statistics are based on a setup which implies . independent coefficients, essentially redu