pcdpca: Dynamic Principal Components for Periodically Correlated Functional Time Series

Method extends multivariate dynamic principal components to periodically correlated multivariate time series.

Version: 0.2.1
Depends: R (≥ 3.3.1)
Imports: freqdom, fda
Published: 2016-11-27
Author: Lukasz Kidzinski [aut, cre], Neda Jouzdani [aut], Piotr Kokoszka [aut]
Maintainer: Lukasz Kidzinski <lukasz.kidzinski at stanford.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
In views: FunctionalData, TimeSeries
CRAN checks: pcdpca results


Reference manual: pcdpca.pdf
Package source: pcdpca_0.2.1.tar.gz
Windows binaries: r-devel: pcdpca_0.2.1.zip, r-release: pcdpca_0.2.1.zip, r-oldrel: pcdpca_0.2.1.zip
OS X El Capitan binaries: r-release: pcdpca_0.2.1.tgz
OS X Mavericks binaries: r-oldrel: pcdpca_0.2.1.tgz


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