Hello, everyone,

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
[1] 107.1164
$sum
[1] 183.4568
```

Unfortunately, I do not know how to interpret this result. Do I have to make differentiation or not?

With kind regards

Luke