您可以修改plot.decomposed.ts
函数(即plot
当你运行时被调度的“方法”plot
在类的对象上decomposed.ts
(这是一个类td
).
getAnywhere(plot.decomposed.ts)
function (x, ...)
{
xx <- x$x
if (is.null(xx))
xx <- with(x, if (type == "additive")
random + trend + seasonal
else random * trend * seasonal)
plot(cbind(observed = xx, trend = x$trend, seasonal = x$seasonal, random = x$random),
main = paste("Decomposition of", x$type, "time series"), ...)
}
请注意,在上面的代码中,该函数对标题进行了硬编码。因此,让我们修改它,以便我们可以选择自己的标题:
my_plot.decomposed.ts = function(x, title="", ...) {
xx <- x$x
if (is.null(xx))
xx <- with(x, if (type == "additive")
random + trend + seasonal
else random * trend * seasonal)
plot(cbind(observed = xx, trend = x$trend, seasonal = x$seasonal, random = x$random),
main=title, ...)
}
my_plot.decomposed.ts(td, "My Title")
这是该图的 ggplot 版本。 ggplot需要数据框,因此第一步是将分解的时间序列转换为数据框形式,然后绘制它。
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))