Package: BayesFM 0.1.7
Rémi Piatek
BayesFM: Bayesian Inference for Factor Modeling
Collection of procedures to perform Bayesian analysis on a variety of factor models. Currently, it includes: "Bayesian Exploratory Factor Analysis" (befa) from G. Conti, S. Frühwirth-Schnatter, J.J. Heckman, R. Piatek (2014) <doi:10.1016/j.jeconom.2014.06.008>, an approach to dedicated factor analysis with stochastic search on the structure of the factor loading matrix. The number of latent factors, as well as the allocation of the manifest variables to the factors, are not fixed a priori but determined during MCMC sampling.
Authors:
BayesFM_0.1.7.tar.gz
BayesFM_0.1.7.tar.gz(r-4.5-noble)BayesFM_0.1.7.tar.gz(r-4.4-noble)
BayesFM.pdf |BayesFM.html✨
BayesFM/json (API)
NEWS
| # Install 'BayesFM' in R: |
| install.packages('BayesFM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:296a80a1a7. Checks:3 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 11 2025 |
| R-4.5-linux-x86_64 | OK | Mar 11 2025 |
| R-4.4-linux-x86_64 | OK | Mar 11 2025 |
Exports:befapost.column.switchpost.sign.switchsimul.dedic.facmodsimul.nfac.priorsimul.R.prior
Dependencies:backportscheckmateclicodacolorspacefansifarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcpprlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| BayesFM: Package for Bayesian Factor Modeling | BayesFM-package BayesFM |
| Bayesian Exploratory Factor Analysis | befa |
| Plot object of class 'befa' | plot.befa |
| Perform column switchting on posterior MCMC sample | post.column.switch |
| Perform sign switchting on posterior MCMC sample | post.sign.switch |
| Generate synthetic data from a dedicated factor model | simul.dedic.facmod |
| Simulate prior distribution of number of latent factors | simul.nfac.prior |
| Simulate prior distribution of factor correlation matrix | simul.R.prior |
| Summarize 'befa' object | summary.befa |
