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Package: pcdpca Title: Dynamic Principal Components for Periodically Correlated Functional Time Series Version: 0.4 Authors@R: c(person("Lukasz", "Kidzinski", email = "firstname.lastname@example.org", role = c("aut", "cre")), person("Neda", "Jouzdani", email = "email@example.com", role = c("aut")), person("Piotr", "Kokoszka", email = "firstname.lastname@example.org", 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 <email@example.com> Repository: CRAN Date/Publication: 2017-09-03 05:17:18 UTC