<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Imputation Methods for Multivariate Locally Stationary Time
Series</dc:title>
  <dc:title>R package mvLSWimpute version 0.1.1</dc:title>
  <dc:subject>CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries)</dc:subject>
  <dc:description>Implementation of imputation techniques based on locally stationary wavelet time series forecasting methods from Wilson, R. E. et al. (2021) &lt;doi:10.1007/s11222-021-09998-2&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: wavethresh, mvLSW</dc:relation>
  <dc:relation>Imports: binhf, xts, zoo, imputeTS, utils</dc:relation>
  <dc:creator>Matt Nunes &lt;nunesrpackages@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Rebecca Wilson [aut],
  Matt Nunes [aut, cre],
  Idris Eckley [ctb, ths],
  Tim Park [ctb]</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2022-08-16</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=mvLSWimpute</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.mvLSWimpute</dc:identifier>
</oai_dc:dc>
