#' Thinning Posterior Draws
#'
#' Thins the MCMC posterior draws in an object of class \code{"dfm"}.
#'
#' @param x an object of class \code{"dfm"}.
#' @param thin an integer specifying the thinning interval between successive values of posterior draws.
#' @param ... further arguments passed to or from other methods.
#'
#' @examples
#'
#' # Load data
#' data("bem_dfmdata")
#'
#' # Generate model data
#' model <- gen_dfm(x = bem_dfmdata, p = 1, n = 1,
#' iterations = 20, burnin = 10)
#' # Number of iterations and burnin should be much higher.
#'
#' # Add prior specifications
#' model <- add_priors(model,
#' lambda = list(v_i = .01),
#' sigma_u = list(shape = 5, rate = 4),
#' a = list(v_i = .01),
#' sigma_v = list(shape = 5, rate = 4))
#'
#' # Obtain posterior draws
#' object <- draw_posterior(model)
#'
#' # Plot factors
#' object <- thin(object, thin = 2)
#'
#' @return An object of class \code{"dfm"}.
#'
#' @export
thin.dfm <- function(x, thin = 10, ...) {
draws <- NA
if (!is.null(x[["lambda"]])) {
draws <- nrow(x[["lambda"]])
}
vars <- c("a", "sigma_u", "sigma_v")
for (i in vars) {
if (is.na(draws)) {
if (!is.null(x[[i]])) {
draws <- nrow(x[[i]])
}
}
}
pos_thin <- seq(from = thin, to = draws, by = thin)
start <- pos_thin[1]
end <- pos_thin[length(pos_thin)]
vars <- c("lambda", "a", "sigma_u", "sigma_v")
for (i in vars) {
if (!is.null(x[[i]])) {
x[[i]] <- coda::mcmc(as.matrix(x[[i]][pos_thin,]), start = start, end = end, thin = thin)
}
}
return(x)
}
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