June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
Content preview from R 语言经典实例（原书第 2 版）
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时间序列分析
｜
451
14.23 均值回归的检验
14.23.1 问题
需要知道所研究的时间序列是否具有均值回归性质（平稳性）。
14.23.2 解决方案
均值回归的常见检验方法是 Augmented Dickey-Fuller 检验（ADF），该检验由 tseries
包的 adf.test 函数实现：
library(tseries)
adf.test(
ts
)
adf.test 的输出包括
p
值。常规地，如果
p
< 0.05，则时间序列可能是均值回归的，
而
p
> 0.05 没有提供这样的证据。
14.23.3 讨论
当时间序列是均值回归时，它往往会回到该序列的长期平均值。它可能会偏离长期均
值，但最终会返回到它的长期均值。如果时间序列不是均值回归，那么它偏离了长期均
值之后可能永远不会回到长期均值。
图 14-18 似乎向上偏离并且不会回到长期均值。来自 adf.test 的较大
p
值证实它不是
均值回归的：
library(tseries)
library(fpp2)
autoplot(goog200)
adf.test(goog200)
#>
#> Augmented Dickey-Fuller Test
#>
#> data: goog200
#> Dickey-Fuller = -2, Lag order = 5, p-value = 0.7
#> alternative hypothesis: stationary
然而，图 14-19 中的时间序列只是在其平均值附近上下波动。较小的
p
值（0.01 ）证实
它是均值回归的： ...
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