The word 'multiscale'can mean many things. However, in this book we are generally
concerned with the representation of objects at a set of scales and then manipulating these …

In this study, we look at the wavelet basis for the nonparametric estimation of density and
regression functions for continuous functional stationary processes in Hilbert space. The …

The present article focuses on the non parametric estimation of multivariate density and
regression functions. We consider the non parametric linear wavelet-based estimators and …

In the present paper, we are mainly concerned with the non parametric estimation of the
density as well as the regression function by using orthonormal wavelet bases. We provide …

This paper investigates the nonparametric linear wavelet-based estimators of multivariate
regression functions. Under mild conditions, we establish the asymptotic normality under the …

We introduce a new approach to shape-preserving estimation of cumulative distribution
functions and probability density functions using the wavelet methodology for multivariate …

We consider the estimation of a density function on the basis of a random sample from a
weighted distribution. We propose linear and nonlinear wavelet density estimators, and …

Empirical Bayes approaches to the shrinkage of empirical wavelet coefficients have
generated considerable interest in recent years. Much of the work to date has focussed on …

The purpose of this note is to introduce and investigate the nonparametric estimation of the
conditional mode using wavelet methods. We propose a new linear wavelet estimator for …

The focus of this article is on studying a partially linear additive model, which is defined
using a measurable function ψ: R q→ R. The model is given as follows: ψ (Y i):= Y i= Z i⊤ …