BayesFM: BayesFM: Package for Bayesian Factor Modeling

In BayesFM: Bayesian Inference for Factor Modeling

BayesFM: Package for Bayesian Factor Modeling

Description

The long-term goal of this package is to provide a collection of procedures to perform Bayesian inference on a variety of factor models.

Details

Currently, this package includes: Bayesian Exploratory Factor Analysis (befa), as developed in Conti et al. (2014), 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 observed variables to the factors, are not fixed a priori but determined during MCMC sampling. More approaches will be included in future releases of this package.

Note

You are very welcome to send me any comments or suggestions for improvements, and to share with me any problems you may encounter with the use of this package.

Author(s)

Rémi Piatek [e-mail]

References

G. Conti, S. Frühwirth-Schnatter, J.J. Heckman, R. Piatek (2014): “Bayesian Exploratory Factor Analysis”, Journal of Econometrics, 183(1), pages 31-57, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jeconom.2014.06.008")}.

BayesFM documentation built on June 22, 2024, 10:24 a.m.