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library(tidyverse) # Includes the packages ggplot2 and tidyr, which we use below
# Get the time values for the time series
Time = attributes(co2)[[1]]
Time = seq(Time[1],Time[2], length.out=(Time[2]-Time[1])*Time[3])
# Convert td to data frame
dat = cbind(Time, with(td, data.frame(Observed=x, Trend=trend, Seasonal=seasonal, Random=random)))
ggplot(gather(dat, component, value, -Time), aes(Time, value)) +
facet_grid(component ~ ., scales="free_y") +
geom_line() +
theme_bw() +
labs(y=expression(CO[2]~(ppm)), x="Year") +
ggtitle(expression(Decomposed~CO[2]~Time~Series)) +
theme(plot.title=element_text(hjust=0.5))
我知道它是關於用ggplot進行時間序列分解的。大部分我需要在第3和第4行上解釋。我想在代碼上應用每月時間系列。請爲我解讀這個r碼
@economia抱歉,這對我來說並不明顯...... –