没有人回复，自己顶了！本人小白，有弱智的地方也请高人点拨哦

建议尝试别的方法建模

子鹿你好，谢谢你的回复！ARIMA模型不适合用于此序列的处理了吗？

If you want to build time series model under ARIMA framework, you have to have a stationary series before doing next steps, because all assumptions about ARIMA model are based upon stationarity. To get a stationary series, you can take difference of the original series. If ADF tests still show non-stationary, you may think of where this non-stationarity comes from. Is it from seasonality, or some outliers? If there is seasonality, you need make necessary seasonal adjustments. If it is because of outliers, you can replace those outliers with exponential smoothing estimates, which can be done by SAS JMP. After getting stationary series, then you can play from there.

如果不平稳的话，需要做平稳化处理，如差分