Imputation Methods for Multivariate Locally Stationary Time Series [R package mvLSWimpute version 0.1.1]

mvLSWimpute: Imputation Methods for Multivariate Locally Stationary Time Series

Implementation of imputation techniques based on locally stationary wavelet time series forecasting methods from Wilson, R. E. et al. (2021) <doi:10.1007/s11222-021-09998-2>.

Version:	0.1.1
Depends:	wavethresh, mvLSW
Imports:	binhf, xts, zoo, imputeTS, utils
Published:	2022-08-16
DOI:	10.32614/CRAN.package.mvLSWimpute
Author:	Rebecca Wilson [aut], Matt Nunes [aut, cre], Idris Eckley [ctb, ths], Tim Park [ctb]
Maintainer:	Matt Nunes <nunesrpackages at gmail.com>
License:	GPL-2
NeedsCompilation:	no
In views:	TimeSeries
CRAN checks:	mvLSWimpute results

Documentation:

Reference manual:

mvLSWimpute.html , mvLSWimpute.pdf

Downloads:

Package source:	mvLSWimpute_0.1.1.tar.gz
Windows binaries:	r-devel: mvLSWimpute_0.1.1.zip, r-release: mvLSWimpute_0.1.1.zip, r-oldrel: mvLSWimpute_0.1.1.zip
macOS binaries:	r-release (arm64): mvLSWimpute_0.1.1.tgz, r-oldrel (arm64): mvLSWimpute_0.1.1.tgz, r-release (x86_64): mvLSWimpute_0.1.1.tgz, r-oldrel (x86_64): mvLSWimpute_0.1.1.tgz

Linking:

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