I am trying to prepare my data for an ARIMA Forecasting. For this purpose, I first applied the BoxCox Transformation. In the next step, I want to test the stationarity.
For this, I first applied the
adf.test(bc_ts). The result:
Augmented Dickey-Fuller Test data: bc_ts Dickey-Fuller = -6.2552, Lag order = 5, p-value = 0.01 alternative hypothesis: stationary Augmented Dickey-Fuller Test data: bc_ts Dickey-Fuller = -6.2552, Lag order = 5, p-value = 0.01 alternative hypothesis: stationary
In the next step I wanted to validate this result with the
kpss-test(bc_ts). However, the result was the following:
KPSS Test for Level Stationarity data: bc_ts KPSS Level = 1.5496, Truncation lag parameter = 4, p-value = 0.01
Since these two results are contradictory to each other, I must, to my knowledge, apply a variance ratio test. I have tried this as follows:
Auto.VR(bc_ts). But the result is the following:
$stat  107.1164 $sum  183.4568
Unfortunately, I do not know how to interpret this result. Do I have to make differentiation or not?
With kind regards