It is not an overstatement to say that statistics is based on various transformations of data. Basic statistical summaries such as the sample mean, variance, z-scores, histograms, etc., are all transformed data. Some more advanced summaries, such as principal components, periodograms, empirical...

It is not an overstatement to say that statistics is based on various transformations of data. Basic statistical summaries such as the sample mean, variance, z-scores, histograms, etc., are all transformed data. Some more advanced summaries, such as principal components, periodograms, empirical...

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...