Perfect simulation for Bayesian wavelet thresholding with correlated coefficients
نویسندگان
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 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, analytically intractable. Nevertheless, it is possible to draw independent samples from a close approximation to the posterior distribution by an approach based on Coupling From The Past, making it possible to use a simulation-based approach to fit the model.
منابع مشابه
Perfect simulation for 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 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 ...
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