The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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.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:

Please use the canonical form https://CRAN.R-project.org/package=mvLSWimpute to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.