pcdpca swMATH ID: 26261 Software Authors: Kidziński, Łukasz; Kokoszka, Piotr; Jouzdani, Neda Mohammadi Description: R package pcdpca: Dynamic Principal Components for Periodically Correlated Functional Time Series. 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>. Homepage: https://cran.r-project.org/web/packages/pcdpca/index.html Source Code: https://github.com/cran/pcdpca Dependencies: R Related Software: R; zoo; foreach; doParallel; Rcpp; RcppArmadillo; Armadillo; BigVAR; freqdom; MTS; xts; gdpc Cited in: 1 Publication Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year Principal components analysis of periodically correlated functional time series. Zbl 1416.62503Kidziński, Łukasz; Kokoszka, Piotr; Jouzdani, Neda Mohammadi 2018 Cited by 3 Authors 1 Jouzdani, Neda Mohammadi 1 Kidziński, Łukasz 1 Kokoszka, Piotr S. Cited in 1 Serial 1 Journal of Time Series Analysis Cited in 1 Field 1 Statistics (62-XX) Citations by Year