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Tip revision: 994e42225542c81cc02708658f24865826071d4c authored by Lukasz Kidzinski on 03 September 2017, 04:17:18 UTC
version 0.4
Tip revision: 994e422
Package: pcdpca
Title: Dynamic Principal Components for Periodically Correlated
        Functional Time Series
Version: 0.4
Authors@R: c(person("Lukasz", "Kidzinski", email = "lukasz.kidzinski@stanford.edu", role = c("aut", "cre")), person("Neda", "Jouzdani", email = "neda.jouzdani@colostate.edu", role = c("aut")), person("Piotr", "Kokoszka", email = "piotr.kokoszka@colostate.edu", role = c("aut")))
Description: Method extends multivariate and functional dynamic principal components
    to periodically correlated multivariate time series. This package allows you to
    compute true dynamic principal components in the presence of periodicity. 
    We follow implementation guidelines as described in Kidzinski, Kokoszka and
    Jouzdani (2017), in Principal component analysis of periodically correlated
    functional time series <arXiv:1612.00040>.
Depends: R (>= 3.3.1)
Imports: freqdom, fda
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-09-03 05:09:05 UTC; lukasz
Author: Lukasz Kidzinski [aut, cre],
  Neda Jouzdani [aut],
  Piotr Kokoszka [aut]
Maintainer: Lukasz Kidzinski <lukasz.kidzinski@stanford.edu>
Repository: CRAN
Date/Publication: 2017-09-03 05:17:18 UTC
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