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#' BayesFM: Package for Bayesian Factor Modeling
#'
#' 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 (\code{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 Rémi Piatek \email{remi.piatek@@gmail.com}
#'
#' @references G. Conti, S. Frühwirth-Schnatter, J.J. Heckman, R. Piatek (2014):
#' ``Bayesian Exploratory Factor Analysis'', \emph{Journal of Econometrics},
#' 183(1), pages 31-57, \doi{10.1016/j.jeconom.2014.06.008}.
#'
#' @docType package
#' @name BayesFM
NULL
.onAttach <- function(libname, pkgname) {
if (interactive() || getOption("verbose")) {
msg <- sprintf(paste(
"###",
"### Package %s (%s) loaded",
"###",
"### Please report any bugs, and send suggestions or feedback",
"### to %s",
"###", sep = "\n"),
pkgname,
utils::packageDescription(pkgname)$Version,
utils::maintainer(pkgname))
packageStartupMessage(msg)
}
}
.onUnload <- function(libpath) {
library.dynam.unload("BayesFM", libpath)
}
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