We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations. The method is illustrated with a ...

We propose a Bayesian hierarchical wavelet methodology for nonparametric regression based on nonlocal priors. Our methodology assumes for the wavelet coefficients a prior that is a mixture of a point ...

An important property of wavelet analysis is perfect reconstruction, which is the process of reassembling a decomposed signal or image into its original form without loss of information.