In an increasingly data-driven world, mathematical tools known as wavelets have become an indispensable way to analyze and understand information. Many researchers receive their data in the form of ...

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 ...