Bayesian Inference for Factor Modeling
BayesFM: Package for Bayesian Factor Modeling
Bayesian Exploratory Factor Analysis
Plot object of class 'befa'
Perform column switchting on posterior MCMC sample
Perform sign switchting on posterior MCMC sample
Generate synthetic data from a dedicated factor model
Simulate prior distribution of number of latent factors
Simulate prior distribution of factor correlation matrix
Summarize 'befa' object
Collection of procedures to perform Bayesian analysis on a variety of factor models. Currently, it includes: "Bayesian Exploratory Factor Analysis" (befa) from G. Conti, S. Frühwirth-Schnatter, J.J. Heckman, R. Piatek (2014) <doi:10.1016/j.jeconom.2014.06.008>, an approach to dedicated factor analysis with stochastic search on the structure of the factor loading matrix. The number of latent factors, as well as the allocation of the manifest variables to the factors, are not fixed a priori but determined during MCMC sampling.