Multivariate Locally Stationary Wavelet Analysis
Tools for analysing multivariate time series with wavelets. This includes: simulation of a multivariate locally stationary wavelet (mvLSW) process from a multivatriate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local coherence and local partial coherence; and, estimation of the asymptotic variance for mvEWS elements. See Park, Eckley and Ombao (2014) <doi:10.1109/TSP.2014.2343937> for details.
c(
person("Simon","Taylor", role=c("aut","cre"), email="s.taylor2@lancaster.ac.uk"),
person("Tim","Park",role="aut",email="t.park@lancaster.ac.uk"),
person("Idris","Eckley",role="ths",email="i.eckley@lancaster.ac.uk"),
person("Rebecca","Killick",role="ctb"))
Simon Taylor [aut, cre],
Tim Park [aut],
Idris Eckley [ths],
Rebecca Killick [ctb]

Multivariate, Locally Stationary Wavelet Process Estimation
Tools for analysing multivariate time series with wavelets. This includes: simulation of a multivariate locally stationary wavelet (mvLSW) process from a multivariate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local coherence and local partial coherence; and, estimation of the asymptotic variance for mvEWS elements. See Park, Eckley and Ombao (2014) <doi:10.1109/TSP.2014.2343937> for details.
R (>= 3.2), fields, wavethresh, xts, zoo

Tools for analysing multivariate time series with wavelets. This includes: simulation of a multivariate locally stationary wavelet (mvLSW) process from a multivariate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local coherence and local partial coherence. See Park, Eckley and Ombao (2014) <doi:10.1109/TSP.2014.2343937> for details.

c(
person("Simon","Taylor", role=c("aut"), email="simon.taylor@ed.ac.uk"),
person("Tim","Park",role="aut",email="t.park@lancaster.ac.uk"),
person("Idris","Eckley",role="ths",email="i.eckley@lancaster.ac.uk"),
person("Rebecca","Killick",role="ctb"),
person("Daniel","Grose",role=c("aut","cre"),email="dan.grose@lancaster.ac.uk")
)
Simon Taylor [aut],
Tim Park [aut],
Idris Eckley [ths],
Rebecca Killick [ctb],
Daniel Grose [aut, cre]