I'm trying to forecast a sequence that looks like below: I know ARIMA, INAR, GLM, etc. but none of these works for this data. Algorithms I found for intermittent time series (ADIDA, Croston, etc.) only output a constant expected value as forecast.
After looking at Cryo's comment, I plotted the 2 graphs he mentioned.
These graphs do seem a lot more "normal" for any model to handle. But I see no obvious trend/seasonality in either of the graphs, and their ACF and PACFs are quite small as well.
So far, I tried the GLM models (negative binomial, binomial, poisson, etc.,) which all gave me predictions of too small variance, and ARIMA (even though the data is integer) which gives me something like below (this one is the "time intervals between peaks" series):
What are some better models/ideas to try to forecast these 2 series? And what level of prediction accuracy should I expect in the end? Is it always possible to make relatively accurate forecasts for a time series? I'm a newbie in series forecasting, thanks a lot for your help...!