我有一个包含预测和置信区间数据的时间序列,我想使用ggplot2同时绘制它们。我是通过以下代码完成的:
set.seed(321)
library(ggplot2)
#create some dummy data similar to mine
sample<-rnorm(350)
forecast<-rnorm(24)
upper<-forecast+2*sd(forecast)
lower<-forecast-2*sd(forecast)
## wrap data into a data.frame
df1 = data.frame(time = seq(325,350,length=26), M = sample[325:350], isin = "observations")
df2 = data.frame(time = seq(351,374,length=24), M = forecast , isin = "my_forecast")
df3 = data.frame(time = seq(351,374,length=24), M = upper ,isin = "upper_bound")
df4 = data.frame(time = seq(351,374,length=24), M = lower, isin = "lower_bound")
df = rbind(df1, df2, df3, df4)
## ggplot object
ggplot(df, aes(x = time, y = M, color = isin)) + geom_line()
如何以一种颜色连接上下线?以及如何设置特定颜色进行预测和采样?
答案 0 :(得分:6)
使用scale_colour_manual
:
ggplot(df, aes(x = time, y = M, color = isin)) + geom_line() +
scale_colour_manual(values=c(observations='blue', my_forecast='red', upper_bound='black', lower_bound='black'))
修改强>
这是另一种选择,受@rnso回答的启发。
ggplot(df1, aes(x = time, y = M)) + geom_line(colour='blue') +
geom_smooth(aes(x=time, y=M, ymax=upper_bound, ymin=lower_bound),
colour='red', data=df5, stat='identity')
答案 1 :(得分:5)
以下可能有用:
ggplot() +
geom_line(data=df1, aes(x = time, y = M, color = isin)) +
stat_smooth(data=df2, aes(x = time, y = M, color = isin))
'method'选项也可用于stat_smooth()