Package: factor.switching
Type: Package
Title: Post-Processing MCMC Outputs of Bayesian Factor Analytic Models
Version: 1.4
Date: 2024-02-12
Authors@R: 
    c(person(given = "Panagiotis",
             family = "Papastamoulis",
             email = "papapast@yahoo.gr",
             role = c( "aut", "cre"),
             comment = c(ORCID = "0000-0001-9468-7613")))
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>
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) <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.  
Imports: coda, HDInterval, lpSolve , MCMCpack
License: GPL-2
NeedsCompilation: no
Packaged: 2024-02-12 12:18:58 UTC; panagiotis
Author: Panagiotis Papastamoulis [aut, cre]
    (<https://orcid.org/0000-0001-9468-7613>)
Repository: CRAN
Date/Publication: 2024-02-12 13:00:02 UTC
Built: R 4.6.0; ; 2026-04-28 02:03:18 UTC; unix
