write some documentation for irf

R/irf.R

@@ -1,8 +1,23 @@
 #' Impulse response functions
 #'
-#' Effect of a shock on the variables over time
+#' Effect of a shock on the factors or variables over time
 #'
-#' @param x An object of type `bayesianVARs_bvar`
+#' @param x An object of type `bayesianVARs_bvar`.
+#' @param shock A vector of shocks. If a factor model was used, then `shock` is
+#'		applied to the factors, and its dimension must be the number of factors.
+#'
+#'		If the Cholesky model was used, then the dimension of `shock` is expected
+#'		to be equals the number of equations. Note that the contemporaneous effects
+#'		of a shock in the Cholesky model depend on the ordering of equations.
+#'
+#' @return Returns a `bayesianVARs_irf` object
+#'
+#' @examples
+#' train_data <- 100 * usmacro_growth[,c("GDPC1", "PCECC96", "GPDIC1", "AWHMAN", "GDPCTPI", "CES2000000008x", "FEDFUNDS", "GS10", "EXUSUKx", "S&P 500")]
+#' prior_sigma <- specify_prior_sigma(data=train_data, type="cholesky")
+#' mod <- bvar(train_data, lags=2L, draws=2000, prior_sigma=prior_sigma)
+#' ir <- irf(mod, shock=c(0,0,0,0,0,0,1,0,0,0))
+#' plot(ir, n_col=2)
 #'
 #' @export
 irf <- function(x, shock, ahead=8) {