如何检查时间序列在 R 中是否平稳？
要检查时间序列是否平稳，我们可以使用adf.testtseries包的函数使用Dickey-Fuller测试。例如，如果我们有一个时间序列对象TimeData然后检查这个时间序列是否静止，我们可以使用命令。adf.test(TimeData)
示例1
x1<-ts(rpois(240,5),frequency=12) x1输出结果
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 3 7 7 1 1 6 5 4 8 5 2 3 2 5 0 3 4 4 3 2 4 6 5 5 4 3 5 8 6 2 3 9 5 4 7 4 4 7 4 2 5 4 5 7 9 9 2 3 2 7 7 5 3 5 3 3 8 2 2 3 5 4 3 7 6 6 6 5 4 6 6 5 6 4 2 7 5 7 5 2 3 7 3 7 7 3 7 4 5 6 8 2 5 6 4 6 5 6 3 5 4 9 3 9 4 4 3 7 8 5 1 7 3 5 4 7 10 4 4 7 9 6 6 8 4 4 4 3 3 11 5 2 5 1 2 6 2 2 5 4 3 6 12 4 7 9 2 8 5 6 3 3 5 4 2 13 7 12 2 3 7 3 1 7 6 8 6 4 14 4 4 6 10 8 9 4 2 7 3 6 9 15 5 5 6 11 2 2 6 5 8 10 6 9 16 5 4 2 3 5 14 4 5 3 9 7 11 17 4 5 6 6 4 10 5 6 3 7 7 3 18 8 7 4 9 4 6 1 2 2 7 5 8 19 8 6 5 2 3 8 8 4 5 3 3 8 20 3 4 4 2 4 2 8 3 5 6 4 4
加载tseries包并测试x1的平稳性-
library(tseries) adf.test(x1)
Augmented Dickey-Fuller Test data: x1 Dickey-Fuller = -5.3203, Lag order = 6, p-value = 0.01 alternative hypothesis: stationary Warning message: In adf.test(x1) : p-value smaller than printed p-value
例2
x2<-ts(rnorm(80),frequency=4) x2输出结果
Qtr1 Qtr2 Qtr3 Qtr4 1 0.60770751 1.51860885 0.42749703 0.68703506 2 0.42218841 0.32858411 0.17599648 0.87994947 3 -1.33761406 0.31770494 -0.47925768 0.97272742 4 -0.37615238 -0.22445651 0.84534205 1.62197957 5 -0.89668820 1.73200007 -0.08857733 1.00659180 6 0.43669956 -1.73037915 -0.20687863 -1.00296218 7 0.63507344 -1.19167403 0.10682158 -0.35904410 8 -0.23533581 1.73153525 0.30313272 0.79616948 9 0.14177702 1.05396871 0.10664840 1.00615408 10 -0.75120735 1.40710169 1.03382332 0.84761125 11 -0.09219708 -2.90114437 0.86964912 0.75207072 12 -1.98357706 0.92872611 -0.59287936 1.10598932 13 -0.24146436 -0.44565952 -0.63415612 -0.28752626 14 -1.98998974 -0.53391601 1.14723658 -1.17779097 15 -0.55899287 0.91836259 0.17393828 2.37323800 16 -0.73209001 0.18996601 -0.60507321 1.48610650 17 -1.38941874 -0.12928990 0.66282081 0.76798462 18 0.27651434 0.36685046 1.35956161 -1.53075985 19 -2.67204336 0.21251039 -1.75949873 -0.33758449 20 1.20913418 0.68987712 2.28974722 1.37072301
测试x2的平稳性-
adf.test(x2)
Augmented Dickey-Fuller Test data: x2 Dickey-Fuller = -3.6685, Lag order = 4, p-value = 0.03288 alternative hypothesis: stationary