#' Thinning Posterior Draws
#'
#' Thins the MCMC posterior draws in an object of class \code{"bvar"}.
#'
#' @param x an object of class \code{"bvar"}.
#' @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("e1")
#' e1 <- diff(log(e1)) * 100
#'
#' # Obtain data matrices
#' model <- gen_var(e1, p = 2, deterministic = 2,
#' iterations = 100, burnin = 10)
#' # Chosen number of iterations and burn-in draws should be much higher.
#'
#' # Add prior specifications
#' model <- add_priors(model)
#'
#' # Obtain posterior draws
#' object <- draw_posterior(model)
#'
#' object <- thin(object)
#'
#' @return An object of class \code{"bvar"}.
#'
#' @export
thin.bvar <- function(x, thin = 10, ...) {
draws <- NA
vars <- c("A0", "A", "B", "C", "Sigma")
for (i in vars) {
if (is.na(draws)) {
if (!is.null(x[[i]])) {
if (x[["specifications"]][["tvp"]][[i]]) {
draws <- nrow(x[[i]][[1]])
} else {
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("A", "A_sigma", "A_lambda",
"B", "B_sigma", "B_lambda",
"C", "C_sigma", "C_lambda",
"A0", "A0_sigma", "A0_lambda",
"Sigma", "Sigma_sigma", "Sigma_lambda")
for (i in vars) {
if (!is.null(x[[i]])) {
if (is.list(x[[i]])) {
for (j in 1:length(x[[i]])) {
x[[i]][[j]] <- coda::mcmc(as.matrix(x[[i]][[j]][pos_thin,]), start = start, end = end, thin = thin)
}
} else {
x[[i]] <- coda::mcmc(as.matrix(x[[i]][pos_thin,]), start = start, end = end, thin = thin)
}
}
}
return(x)
}
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