R中的历史方差误差分解图

Question

我在下面的链接中找到了如何估计 R 中 VAR 模型的历史方差分解

Historical Variance Error Decompotision Daniel Ryback

Daniel Ryback 在 excel 图中显示结果，但我想用 ggplot 准备它，所以我创建了一些线来获得它，但是，我在 ggplot 中得到的图与 Daniel 在 Excel 中显示的图非常不同。我在 excel 中复制并得到与 Daniel 相同的结果，所以我准备 ggplot 的方式似乎存在错误。有没有人建议得出 excel 结果？

见下面我的代码

library(vars)
library(ggplot2)
library(reshape2)

此代码是在运行上面链接中 Daniel Ryback 开发的代码定义 HD 功能后运行的

data(Canada)
ab<-VAR(Canada, p = 2, type = "both")
HD <- VARhd(Estimation=ab)
HD[,,1] 

ex <- HD[,,1]
ex1 <- as.data.frame(ex) # transforming the HD matrix as data frame #
ex2 <- ex1[3:84,1:4] # taking our the first 2 rows as they are N/As #
colnames(ex2) <- c("Emplyment", "Productivity", "Real Wages", "Unemplyment") # renaming columns #
ex2$Period <- 1:nrow(ex2) # creating an id column #
col_id <- grep("Period", names(ex2)) # setting the new variable as id #
ex3 <- ex2[, c(col_id, (1:ncol(ex2))[-col_id])] # moving id variable to the first column #
molten.ex <- melt(ex3, id = "Period") # melting the data frame #

ggplot(molten.ex, aes(x = Period, y = value, fill = variable)) + 
geom_bar(stat = "identity") + 
guides(fill = guide_legend(reverse = TRUE))

ggplot 版本

Excel 版本

Answer 1

不同之处在于ggplot2 对variable 因子进行排序，并以与excel 不同的顺序绘制它。如果在绘制之前重新排序因子，它将把“失业”放在底部，将“就业”放在顶部，就像在 excel 中一样：

molten.ex$variable <- factor(molten.ex$variable, levels = c("Unemployment",
                                                "Real Wages",
                                                "Productivity",
                                                "Employment"))

ggplot(molten.ex, aes(x = Period, y = value, fill = variable)) + 
  geom_bar(stat = "identity", width = 0.6) + 
  guides(fill = guide_legend(reverse = TRUE)) +
  # Making the R plot look more like excel for comparison... 
  scale_y_continuous(limits = c(-6,8), breaks = seq(-6,8, by = 2)) +
  scale_fill_manual(name = NULL, 
                    values = c(Unemployment = "#FFc000",  # yellow
                               `Real Wages` = "#A4A4A4",  # grey
                               Productivity = "#EC7C30",  # orange
                               Employment = "#5E99CE")) + # blue
  theme(rect = element_blank(),
        panel.grid.major.y = element_line(colour = "#DADADA"),
        legend.position  = "bottom",
        axis.ticks = element_blank(),
        axis.title = element_blank(),
        legend.key.size = unit(3, "mm"))

给予：

大致匹配 Daniel Ryback 帖子中的 excel 图：