What should be the P-value in ADF test?

The p-value is obtained is greater than significance level of 0.05 and the ADF statistic is higher than any of the critical values. Clearly, there is no reason to reject the null hypothesis. So, the time series is in fact non-stationary.

How do you check for stationarity in R?

To check if a time series is stationary, we can use Dickey-Fuller test using adf. test function of tseries package. For example, if we have a time series object say TimeData then to check whether this time series is stationary or not we can use the command adf. test(TimeData).

What library is ADF test in R?

urca R library
df : ADF test function in urca R library. ur. df() function urca R library performs the ADF unit root test, which has the next specification. In particular, when we use selectlags parameters, lag order of lagged dependent variable is automatically selected.

Why is the ADF test preferred to the DF test?

The primary differentiator between the two tests is that the ADF is utilized for a larger and more complicated set of time series models. The augmented Dickey-Fuller statistic used in the ADF test is a negative number. The more negative it is, the stronger the rejection of the hypothesis that there is a unit root.

What is lag order in ADF test?

The A in ADF means that the test is augmented by the addition of lags. The selection of the number of lags in ADF can be done in different ways. A common way is to start with a large number of lags selected a priori and reduce the number of lags sequentially until the longest lag is statistically significant.

Which package is ADF test in?

R package
The ADF Test is a common statistical test to determine whether a given time series is stationary or not. We explain the interpretation of ADF test results from R package by making the meaning of the alphanumeric name of test statistics clear.