#' @title Print method for \code{bayesFst} objects
#'
#' @description Provides a simple summary of the input data used with this package.
#'
#' @param x An object of class \code{bayesFstData}.
#' @param \ldots Not used.
#'
#' @export
#' @seealso readData
print.bayesFst = function(x, ...){
cat("This object provides the input parameters and data for the Bayesian estimation\n")
cat("of Fst. The model is\n\n")
cat("\tlogit(Fst[i,j]) = alpha[i] + beta[j]")
if(x$b$interaction){
cat(" + gamma[i,j]\n\n")
}else{
cat("\n\n")
}
cat("where:\n")
cat("\talpha[i] is the effect for locus i,\n")
cat("\tbeta[j] is the effect for population j")
if(x$b$interaction){
cat(",\n\tgamma[i,j] is the effect for locus i in population j\n")
}else{
cat(".\n")
}
cat("\nThe current priors are:\n\n")
l = x$b$getPriorParams()
cat(sprintf(" alpha[i] ~ N(%.2f, %.2f^2),\n", l$alpha[1], l$alpha[2]))
cat(sprintf(" beta[i] ~ N(%.2f, %.2f^2)", l$beta[1], l$beta[2]))
if(x$b$interaction){
cat(sprintf(",\ngamma[i,j] ~ N(%.2f, %.2f^2),\n\n", l$gamma[1], l$gamma[2]))
}else{
cat(".\n\n")
}
cat(sprintf("The scale parameter for Normal updates is %.2f\n", l$uSigma))
cat(sprintf("The scale parameter for Dirichlet updates of p[i,j] is %.2f\n", l$pSigma))
cat(sprintf("The correlation parameter (fixed) between adjacent loci is %.2f\n\n", l$cor))
x$b$printRunInfo()
cat("\nData has ")
if(!x$b$isDataLoaded()){
cat("not ")
}
cat("been loaded.\n")
}
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