TwoStepSDFM: Estimate a Sparse Mixed Frequency Gaussian Factor Model Using a Two-Step Procedure

Estimate a sparse Gaussian state-space model with mixed frequency data via sparse principal components analysis and the Kalman filter and smoother. For more details see Franjic and Schweikert (2024) <doi:10.2139/ssrn.4733872>.

Version: 0.2.0
Depends: R (≥ 4.0)
Imports: Rcpp (≥ 1.0.8), zoo, xts, lubridate, ggplot2, patchwork, doSNOW, doParallel, foreach, parallel, Rdpack, grDevices, withr
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-04-21
DOI: 10.32614/CRAN.package.TwoStepSDFM (may not be active yet)
Author: Domenic Franjic [aut, cre]
Maintainer: Domenic Franjic <franjic at uni-hohenheim.de>
License: GPL-3
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: TwoStepSDFM results

Documentation:

Reference manual: TwoStepSDFM.html , TwoStepSDFM.pdf
Vignettes: Introduction to TwoStepSDFM (source, R code)

Downloads:

Package source: TwoStepSDFM_0.2.0.tar.gz
Windows binaries: r-devel: not available, r-release: TwoStepSDFM_0.2.0.zip, r-oldrel: TwoStepSDFM_0.2.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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