Package: factor.switching
Type: Package
Title: Post-Processing MCMC Outputs of Bayesian Factor Analytic Models
Version: 1.1
Date: 2020-04-14
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 (2020) <arXiv:2004.05105>) 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
License: GPL-2
NeedsCompilation: no
Packaged: 2020-04-15 05:50:45 UTC; mqbssppe
Author: Panagiotis Papastamoulis [aut, cre]
    (<https://orcid.org/0000-0001-9468-7613>)
Repository: CRAN
Date/Publication: 2020-04-15 08:30:06 UTC
