将ggfortify自动绘图与更改点包函数(cpt.meanvar)相结合

Question

我正在使用ggfortify包中的autoplot函数来绘制带有预测和拟合的时间序列图，下面是我是如何做的

library(forecast)
library(ggplot2)
library(ggfortify)
fc <- forecast(fdeaths)
autoplot(fc)
autoplot(fc) + geom_line(aes(y = fitted(fc)), col = "red")

现在我想在上面的图中显示均值发生变化的时间段，以及在位移之前和之后的均值

我可以使用'changepoint‘包单独完成，语法如下

library(changepoint)
autoplot(cpt.mean(fdeaths))

plot(cpt.mean(fdeaths),cpt.col='blue')

所有这些的组合视图将提供非常强大的洞察力，请求帮助

]1

Answer 1

这里有一个小例子。但是，它必须自动循环绘制线段(geom_segment)和vline (geom_vline)。

library(forecast)
library(ggplot2)
library(ggfortify)
library(changepoint)
library(lubridate)

fc <- forecast(fdeaths)
cp <- changepoint::cpt.mean(fdeaths)
plot(cp,cpt.col='blue')
# plot(x = 1:length(c(fdeaths)), y = c(fdeaths), type = "l")
Vikram <- data.frame(ts = c(fdeaths),
                     Obs = seq(lubridate::ymd('1974-01-01'),
                               lubridate::ymd('1979-12-01'), by = "1 month"),
                     fitted = fitted(fc))
Vikram_md <- changepoint::param.est(cp)[[1]] # mean
# cp@cpts  # change-points
cp_ <- cp@cpts

autoplot(fc) + geom_line(aes(y = fitted(fc)), col = "red") +
  geom_segment(x = Vikram$Obs[1], 
               y = Vikram_md[1], yend = Vikram_md[1],
               xend = Vikram$Obs[1] %m+% months(cp_[1]), 
               size = 1.2, col = "blue") +
  geom_segment(x = Vikram$Obs[1] %m+% months(cp_[1]), 
               y = Vikram_md[2], yend = Vikram_md[2],
               xend = Vikram$Obs[1] %m+% months(cp_[2]), 
               size = 1.2, col = "blue") +
  geom_vline(aes(xintercept = Vikram$Obs[1] %m+% months(cp_[2])),
             linetype = "dashed", colour = "red")

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