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Can anyone please clarify for me the differences between ADF(Augmented Dickey-Fuller) and KPSS (Kwiatkowski–Phillips–Schmidt–Shin) tests in testing the stationarity of a time series?

I tested my time series with both of them and they gave me contradictory results.

An interpretation of each test definition would be so helpful for me.

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    $\begingroup$ Questions about interpretations of statistical tests are not really programming questions. Thus they would be a better fit for Cross Validated where questions about statistical methods are on-topic rather than Stack Overflow. But either way, questions are easier to answer if you give a specific example with sample data to work with. $\endgroup$
    – MrFlick
    Commented Dec 28, 2015 at 17:01

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i think that adf test and KPSS test have the same objectif in fact adf test show if your time series is stationary or not so if your p value <0.05( level 5%) means that you reject H0 so your time series is stationary

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  • $\begingroup$ Thank you for you answer. Can you please make it more clear. I don't really get the difference between these two tests especially that they gave me contradictory results. $\endgroup$
    – Sarah
    Commented Dec 28, 2015 at 17:16

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