Signals with irregular sampling structures arise naturally in many fields. In applications such as spectral decomposition and nonparametric regression, classical methods often assume a regular samplin
This article is motivated by several articles that propose statistical inference where the independence of wavelet coefficients for both short- as well as long-range dependent time series is assumed.
High-dimensional multivariate nonstationary time series, i.e. data whose second order properties vary over time, are common in many scientific and industrial applications. In this article we propose a
