Estimate a Sparse Mixed Frequency Gaussian Factor Model Using a Two-Step Procedure R package TwoStepSDFM version 0.2.0 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>. Software 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) Domenic Franjic <franjic@uni-hohenheim.de> Comprehensive R Archive Network (CRAN) Domenic Franjic [aut, cre] GPL-3 2026-04-21 application/tgz https://CRAN.R-project.org/package=TwoStepSDFM doi:10.32614/CRAN.package.TwoStepSDFM