Package: dipca
Type: Package
Title: Dynamic Inner Principal Component Analysis
Version: 0.1.0
Authors@R: person(
    given = c("Bradley", "R."),
    family = "Buchsbaum",
    role = c("aut", "cre", "cph"),
    email = "brad.buchsbaum@gmail.com")
Description: Methods for dynamic inner principal component analysis
        (DiPCA), dynamic inner canonical correlation analysis (DiCCA),
        and dynamic inner partial least squares (DiPLS) for
        multivariate time series. These methods extract latent
        components that follow autoregressive models, enabling temporal
        prediction and reconstruction. Based on Dong and Qin (2018)
        <doi:10.1016/j.jprocont.2017.05.002>, Dong and Qin (2018)
        <doi:10.1016/j.ifacol.2018.09.379>, and Dong and Qin (2018)
        <doi:10.1016/j.jprocont.2018.04.006>. Integrates with the
        'multivarious' package for consistent preprocessing and
        projection interfaces.
License: GPL (>= 3) + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://github.com/bbuchsbaum/dipca
BugReports: https://github.com/bbuchsbaum/dipca/issues
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), multivarious (>= 0.3.0), stats, forecast
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.3.3
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2, gridExtra,
        reshape2
Config/testthat/edition: 3
VignetteBuilder: knitr
Repository: https://bbuchsbaum.r-universe.dev
Date/Publication: 2026-06-25 00:25:13 UTC
RemoteUrl: https://github.com/bbuchsbaum/dipca
RemoteRef: HEAD
RemoteSha: d82339a377e41c41fff7954b9921c1bea2cb65f7
NeedsCompilation: yes
Packaged: 2026-06-25 05:17:42 UTC; root
Author: Bradley R. Buchsbaum [aut, cre, cph]
Maintainer: Bradley R. Buchsbaum <brad.buchsbaum@gmail.com>