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factor.switching  

Post-Processing MCMC Outputs of Bayesian Factor Analytic Models
View on CRAN: Click here


Download and install factor.switching package within the R console
Install from CRAN:
install.packages("factor.switching")

Install from Github:
library("remotes")
install_github("cran/factor.switching")

Install by package version:
library("remotes")
install_version("factor.switching", "1.4")



Attach the package and use:
library("factor.switching")
Maintained by
Panagiotis Papastamoulis
[Scholar Profile | Author Map]
First Published: 2020-03-11
Latest Update: 2024-02-12
Description:
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) ) 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.
How to cite:
Panagiotis Papastamoulis (2020). factor.switching: Post-Processing MCMC Outputs of Bayesian Factor Analytic Models. R package version 1.4, https://cran.r-project.org/web/packages/factor.switching. Accessed 31 Mar. 2025.
Previous versions and publish date:
1.0 (2020-03-11 17:00), 1.1 (2020-04-15 10:30), 1.2 (2021-07-13 00:10), 1.3 (2022-03-16 12:20)
Other packages that cited factor.switching R package
View factor.switching citation profile
Other R packages that factor.switching depends, imports, suggests or enhances
Complete documentation for factor.switching
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