I have a time series without significant autocorrelation.
Here you can find a year worth of data and a forecast produced by
auto.arima from the
observed and predicted values
I have tried multiple models, for example ANNs and SVR, but they seem to always predict the most frequent values of the series. In other words the forecasts are nearly straight lines near the series mean value.
Also I tried to use the
ets R framework, but the forecasts were not much different from
All models were validated using rolling out of sample forecasts.
No model achieved an R2 score over 0.1. I aim to minimize the mean absolute error, the best I got was 1. My question is: What methods are there for forecasting such time series?