Package: factor.switching 1.4
factor.switching: Post-Processing MCMC Outputs of Bayesian Factor Analytic Models
A well known identifiability issue in factor analytic models is the invariance with respect to orthogonal transformations. This problem burdens the inference under a Bayesian setup, where Markov chain Monte Carlo (MCMC) methods are used to generate samples from the posterior distribution. The package applies a series of rotation, sign and permutation transformations (Papastamoulis and Ntzoufras (2022) <doi:10.1007/s11222-022-10084-4>) into raw MCMC samples of factor loadings, which are provided by the user. The post-processed output is identifiable and can be used for MCMC inference on any parametric function of factor loadings. Comparison of multiple MCMC chains is also possible.
Authors:
factor.switching_1.4.tar.gz
factor.switching_1.4.zip(r-4.5)factor.switching_1.4.zip(r-4.4)factor.switching_1.4.zip(r-4.3)
factor.switching_1.4.tgz(r-4.4-any)factor.switching_1.4.tgz(r-4.3-any)
factor.switching_1.4.tar.gz(r-4.5-noble)factor.switching_1.4.tar.gz(r-4.4-noble)
factor.switching_1.4.tgz(r-4.4-emscripten)factor.switching_1.4.tgz(r-4.3-emscripten)
factor.switching.pdf |factor.switching.html✨
factor.switching/json (API)
# Install 'factor.switching' in R: |
install.packages('factor.switching', repos = c('https://mqbssppe.r-universe.dev', 'https://cloud.r-project.org')) |
- small_posterior_2chains - Example data
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:aba479e72b. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-win | OK | Nov 16 2024 |
R-4.5-linux | OK | Nov 16 2024 |
R-4.4-win | OK | Nov 16 2024 |
R-4.4-mac | OK | Nov 16 2024 |
R-4.3-win | OK | Nov 16 2024 |
R-4.3-mac | OK | Nov 16 2024 |
Exports:compareMultipleChainscredible.regionplot.rspprocrustes_switchingrsp_exactrsp_full_sarsp_partial_saswitch_and_permuteweighted_procrustes_switching
Dependencies:codaHDIntervallatticelpSolveMASSMatrixMatrixModelsmcmcMCMCpackquantregSparseMsurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Post-Processing MCMC Outputs of Bayesian Factor Analytic Models | factor.switching-package factor.switching |
Compare multiple chains | compareMultipleChains |
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter. | credible.region |
Plot posterior means and credible regions | plot.rsp |
Orthogonal Procrustes rotations | procrustes_switching |
Rotation-Sign-Permutation (RSP) algorithm (Exact scheme) | rsp_exact |
Rotation-Sign-Permutation (RSP) algorithm (Full Simulated Annealing) | rsp_full_sa |
Rotation-Sign-Permutation (RSP) algorithm (Partial Simulated Annealing) | rsp_partial_sa |
Example data | small_posterior_2chains |
Apply sign switchings and column permutations | switch_and_permute |
Weighted Orthogonal Procrustes rotations | weighted_procrustes_switching |