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 postprocessed 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.
Package details 


Author  Panagiotis Papastamoulis [aut, cre] (<https://orcid.org/0000000194687613>) 
Maintainer  Panagiotis Papastamoulis <papapast@yahoo.gr> 
License  GPL2 
Version  1.1 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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