We propose a wavelet-based denoising methodology based on total energy of a neighboring pair of coefficients plus their “parental” coefficient. The model is based on a Bayesian hierarchical model using a contaminated exponential prior on the total mean energy in a neighborhood of wavelet...

A wavelet-based multifractal spectrum (MFS) for the analysis of images that possess an erratically changing oscillatory behavior at various scales is constructed and estimated. The methodology is applied to the analysis of mammograms. The key contribution is that the analysis is not focused on...

To estimate a possibly multivariate regression function g under the general regression setup, y=g+ϵ, one can use wavelet thresholding as an alternative to conventional nonparametric regression methods. Wavelet thresholding is a simple operation in the wavelet domain that selects a subset of...

This article studies tests for assessing whether two stationary and independent time series have the same dynamics - specifically, whether the autocovariances of both series coincide at all lags. Frequency domain statistics previously proposed for this purpose are reviewed. A time domain...

In this work, we discuss Bayesian estimation of multinomial probabilities associated with a finite alphabet A under incomplete experimental information. Two types of prior information are considered: (i) number of letters needed to see a particular pattern for the first time, and (ii) the fact...

It is a well-known fact that any orthonormal basis in L2 can produce a "random density". If {[phi]n} is an orthonormal basis and {an} is a sequence of random variables such that [Sigma] an2 = 1 a.s., then [latin small letter f with hook](x) = [Sigma] an[phi]n(x)2 is a random density. In this...