Wavelet-based and Fourier-based multivariate Whittle estimation: multiwave
Abstract
Multivariate time series with long-dependence are observed in many applications such as finance , geophysics or neuroscience. Many packages provide estimation tools for univariate settings but few are addressing the problem of long-dependence estimation for multivariate settings. The package multiwave is providing efficient estimation procedures for multivariate time series. Two semi-parametric estimation methods of the long-memory exponents and long-run covariance matrix of time series are implemented. The first one is the Fourier-based estimation proposed by [18] and the second one is a wavelet-based estimation described in [4]. The objective of this paper is to provide an overview of the R package multiwave with its practical application perspectives.
Keywords
Cite
@article{arxiv.1811.10224,
title = {Wavelet-based and Fourier-based multivariate Whittle estimation: multiwave},
author = {Sophie Achard and Irène Gannaz},
journal= {arXiv preprint arXiv:1811.10224},
year = {2018}
}