A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet shrinkage using cross - validation

Wavelets are orthonormal basis functions with special properties that show potential in many areas of mathematics and statistics. This article concentrates on the estimation of functions and images from noisy data using wavelet shrinkage. A modified form of twofold cross-validation is introduced to choose a threshold for wavelet shrinkage estimators operating on data sets of length a power of t...

A Step-Down Test for Effects in Unreplicated Factorial Trials

A Fisherian Detour of the Step-down Procedure

In a Step-down procedure, apart from an hierarchy of the component hypotheses (leading to the steps), one also needs to settle on, their individual levels of significnace (constrained on the overall one). The Fisher method of combining independent tests is extended to the step-down procedure and its Bahadur-efficiency and (asymptotic) optimality results are considered.

Wavelet shrinkage using adaptive structured sparsity constraints

Structured sparsity approaches have recently received much attention in the statistics, machine learning, and signal processing communities. A common strategy is to exploit or assume prior information about structural dependencies inherent in the data; the solution is encouraged to behave as such by the inclusion of an appropriate regularization term which enforces structured sparsity constrain...

Wavelet Shrinkage for Nonequispaced Samples

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