# SARIMA nonstationary: how to remove trend and seasonality?

I have a database with hourly records. When I perform my ADF and KPSS test the p-value is less than alpha 0.05 so the series is assumed to be stationary. But by plotting the ACF the delays are all out it shows that the series is not stationary. with two or more differentiation still can't remove the trend and seasonality! someone has already found this problem!

• A low p-value of the KPSS tests suggests nonstationarity. ADF test suggests lack of a unit root, hence no differencing is needed. Why would you think differencing should help? Significant values of ACF do not imply nonstationarity. Since you mention SARIMA, why don't you let auto.arima in R pick a model for you? The model will take care of stochastic and (simple forms of) deterministic trends as well as seasonality. Mar 14 '20 at 10:22
• thanks for your answer @RichardHardy. I'm sending you my results. I don't think they're right. stat ADF = -6.349416230014464 p-value = 2.6333871594962958e-08 and stat KPSS = 10.18962466162416 p-value = 0.01 Mar 14 '20 at 10:49
• with pm.ato_arima I had SARIMAX(13, 2, 1) Log Likelihood -24612.451 Mar 14 '20 at 10:56
• sarima because I have seosonality 24*7 (hours and days) Mar 14 '20 at 11:07