Package: dfms
Version: 1.0.1
Title: Dynamic Factor Models
Authors@R: c(person("Sebastian", "Krantz", role = c("aut", "cre"), email = "sebastian.krantz@graduateinstitute.ch"),
             person("Rytis", "Bagdziunas", role = "aut"),
             person("Santtu", "Tikka", role = "rev"),
             person("Eli", "Holmes", role = "rev"), 
             person("Christian", "Klettner", role = "ctb"))
Description: Efficient estimation of Dynamic Factor Models using the
        Expectation Maximization (EM) algorithm or Two-Step (2S)
        estimation, supporting datasets with missing data and
        mixed-frequency nowcasting applications. Factors follow a
        stationary VAR process of order p. Estimation options include:
        running the Kalman Filter and Smoother once with PCA initial
        values (2S) as in Doz, Giannone and Reichlin (2011)
        <doi:10.1016/j.jeconom.2011.02.012>; iterated Kalman Filtering
        and Smoothing until EM convergence as in Doz, Giannone and
        Reichlin (2012) <doi:10.1162/REST_a_00225>; or the adapted EM
        algorithm of Banbura and Modugno (2014) <doi:10.1002/jae.2306>,
        allowing arbitrary missing-data patterns and monthly-quarterly
        mixed-frequency datasets. The implementation uses the
        'Armadillo' 'C++' library and the 'collapse' package for fast
        estimation. A comprehensive set of methods supports
        interpretation and visualization, forecasting, and
        decomposition of the 'news' content of macroeconomic data
        releases following Banbura and Modugno (2014). Information
        criteria to choose the number of factors are also provided,
        following Bai and Ng (2002) <doi:10.1111/1468-0262.00273>.
URL: https://docs.ropensci.org/dfms/, https://github.com/ropensci/dfms
BugReports: https://github.com/ropensci/dfms/issues
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.1), collapse (>= 2.0.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: xts, vars, magrittr, testthat (>= 3.0.0), knitr, rmarkdown,
        covr, dlm, KFAS
License: GPL-3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd",
        "srr::srr_stats_roclet"))
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
Repository: https://ropensci.r-universe.dev
Date/Publication: 2026-06-18 20:43:41 UTC
RemoteUrl: https://github.com/ropensci/dfms
RemoteRef: main
RemoteSha: 137a9a8d5a608a3e95f4015956be8742e2a789b1
NeedsCompilation: yes
Packaged: 2026-06-18 22:07:44 UTC; root
Author: Sebastian Krantz [aut, cre],
  Rytis Bagdziunas [aut],
  Santtu Tikka [rev],
  Eli Holmes [rev],
  Christian Klettner [ctb]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>