Popular wavelet models. (English) Zbl 1144.62304
Summary: The modern approach for wavelets imposes a Bayesian prior model on the wavelet coefficients to capture the sparseness of the wavelet expansion. The idea is to build flexible probability models for the marginal posterior densities of the wavelet coefficients. We derive exact expressions for two popular models for the marginal posterior density. We also illustrate the superior performance of these models over the standard models for wavelet coefficients.
MSC:
| 62E15 | Exact distribution theory in statistics |
| 62F15 | Bayesian inference |
| 65T60 | Numerical methods for wavelets |
| 33C90 | Applications of hypergeometric functions |
| 62E99 | Statistical distribution theory |
References:
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