{ "_id": "6a6c37173388593b7e8cc6eb", "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\"),\nperson(\"Rytis\", \"Bagdziunas\", role = \"aut\"),\nperson(\"Santtu\", \"Tikka\", role = \"rev\"),\nperson(\"Eli\", \"Holmes\", role = \"rev\"),\nperson(\"Christian\", \"Klettner\", role = \"ctb\"))", "Description": "Efficient estimation of Dynamic Factor Models using the\nExpectation Maximization (EM) algorithm or Two-Step (2S)\nestimation, supporting datasets with missing data and\nmixed-frequency nowcasting applications. Factors follow a\nstationary VAR process of order p. Estimation options include:\nrunning the Kalman Filter and Smoother once with PCA initial\nvalues (2S) as in Doz, Giannone and Reichlin (2011)\n; iterated Kalman Filtering\nand Smoothing until EM convergence as in Doz, Giannone and\nReichlin (2012) ; or the adapted EM\nalgorithm of Banbura and Modugno (2014) ,\nallowing arbitrary missing-data patterns and monthly-quarterly\nmixed-frequency datasets. The implementation uses the\n'Armadillo' 'C++' library and the 'collapse' package for fast\nestimation. A comprehensive set of methods supports\ninterpretation and visualization, forecasting, and\ndecomposition of the 'news' content of macroeconomic data\nreleases following Banbura and Modugno (2014). Information\ncriteria to choose the number of factors are also provided,\nfollowing Bai and Ng (2002) .", "URL": "https://docs.ropensci.org/dfms/, https://github.com/ropensci/dfms", "BugReports": "https://github.com/ropensci/dfms/issues", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE, roclets = c (\"namespace\", \"rd\",\n\"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": { "Date": "2026-07-31 05:34:31 UTC", "User": "root" }, "Author": "Sebastian Krantz [aut, cre],\nRytis Bagdziunas [aut],\nSanttu Tikka [rev],\nEli Holmes [rev],\nChristian Klettner [ctb]", "Maintainer": "Sebastian Krantz ", "_user": 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