Perfect simulation for wavelet thresholding with correlated coefficients
نویسنده
چکیده
We introduce a new method of Bayesian wavelet shrinkage for reconstructing a signal when we observe a noisy version. Rather than making the usual assumption that the wavelet coefficients of the signal are independent, we assume that they are locally correlated in both location (time) and scale (frequency). This leads us to prefer a novel prior structure to which is, unfortunately, analytically intractable. We demonstrate that it is possible to draw exact, independent samples from the posterior distribution using Coupling From The Past, making a simulation-based approach possible.
منابع مشابه
Perfect simulation for Bayesian wavelet thresholding with correlated coefficients
We introduce a new method of Bayesian wavelet shrinkage for reconstructing a signal when we observe a noisy version. Rather than making the usual assumption that the wavelet coefficients of the signal are independent, we allow for the possibility that they are locally correlated in both location (time) and scale (frequency). This leads us to a prior structure which is, unfortunately, analytical...
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