Package: TwoStepSDFM 0.3.0

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>.

Authors:Domenic Franjic [aut, cre]

TwoStepSDFM_0.3.0.tar.gz
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TwoStepSDFM_0.3.0.tgz(r-4.6-x86_64)TwoStepSDFM_0.3.0.tgz(r-4.6-arm64)TwoStepSDFM_0.3.0.tgz(r-4.5-x86_64)TwoStepSDFM_0.3.0.tgz(r-4.5-arm64)
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TwoStepSDFM_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TwoStepSDFM/json (API)

# Install 'TwoStepSDFM' in R:

install.packages('TwoStepSDFM', repos = c('https://sisanchopancho.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sisanchopancho/twostepsdfm/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

factor_model - Example factor model dataset
mixed_freq_factor_model - Mixed-frequency factor model dataset

On CRAN:

cpp

4.88 score 1 stars 3 scripts 459 downloads 9 exports 34 dependencies

Last updated from:7c51f77484. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	299
linux-devel-x86_64	OK	303
source / vignettes	OK	446
linux-release-arm64	OK	327
linux-release-x86_64	OK	256
macos-release-arm64	OK	210
macos-release-x86_64	OK	489
macos-oldrel-arm64	OK	324
macos-oldrel-x86_64	OK	473
windows-devel	OK	356
windows-release	OK	371
windows-oldrel	OK	339
wasm-release	OK	236

Exports:crossVal imputeMonthlyData kalmanFilterSmoother noOfFactors nowcast simFM sparsePCA twoStepDenseDFM twoStepSDFM

Dependencies:cli codetools cpp11 doParallel doSNOW farver foreach generics ggplot2 glue gtable isoband iterators labeling lattice lifecycle lubridate patchwork R6 rbibutils RColorBrewer Rcpp RcppEigen Rdpack rlang S7 scales snow timechange vctrs viridisLite withr xts zoo

Introduction to TwoStepSDFM

Rendered fromIntroTwoStepSDFM.Rmdusingknitr::rmarkdown

Last update: 2026-05-12
Started: 2025-11-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Cross-validate SDFM Hyper-Parameters	crossVal
Example factor model dataset	factor_model
Impute monthly data.	imputeMonthlyData
Univariate Representation of the Multivariate Kalman Filter and Smoother	kalmanFilterSmoother
Mixed-frequency factor model dataset	mixed_freq_factor_model
Estimate the number of Factors	noOfFactors
Predict Mixed-Frequency Data via Dynamic Factor Models	nowcast
Generic plotting function for KFSFit S3 objects	plot.KFSFit
Generic plotting function for NoOfFactorsFit S3 objects	plot.NoOfFactorsFit
Generic plotting function for SDFMcrossVal S3 objects	plot.SDFMcrossVal
Generic plotting function for SDFMFit S3 objects	plot.SDFMFit
Generic plotting function for SDFMnowcast S3 objects	plot.SDFMnowcast
Generic plotting function for SimulData S3 objects	plot.SimulData
Generic plotting function for SPCAFit S3 objects	plot.SPCAFit
Generic prediction function for 'SDFMFit' S3 objects	predict.SDFMFit
Generic printing function for KFSFit S3 objects	print.KFSFit
Generic printing function for NoOfFactorsFit S3 objects	print.NoOfFactorsFit
Generic print function for SDFMcrossVal S3 objects	print.SDFMcrossVal
Generic printing function for SDFMFit S3 objects	print.SDFMFit
Generic print function for SDFMnowcast S3 objects	print.SDFMnowcast
Generic printing function for SimulData S3 objects	print.SimulData
Generic printing function for SPCAFit S3 objects	print.SPCAFit
Simulate Dynamic Factor Models.	simFM
Sparse Principal Components Analysis	sparsePCA
Two Step Dense Dynamic Factor Model Estimator.	twoStepDenseDFM
Two Step Sparse Dynamic Factor Model Estimator.	twoStepSDFM