Package: mvLSW
Type: Package
Title: Multivariate, Locally Stationary Wavelet Process Estimation
Version: 1.2.5
Date: 2022-06-14
Authors@R: 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")
	)
Description: 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.
Depends: R (>= 3.2),fields, wavethresh, xts, zoo,methods
License: GPL (>= 3)
NeedsCompilation: yes
Packaged: 2022-06-14 15:19:28 UTC; grosedj
Author: Simon Taylor [aut],
  Tim Park [aut],
  Idris Eckley [ths],
  Rebecca Killick [ctb],
  Daniel Grose [aut, cre]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2022-06-14 15:40:02 UTC
RoxygenNote: 7.1.2
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 06:36:20 UTC; unix
Archs: mvLSW.so.dSYM
