I have a time series of data of when 'data events' are going to happen.
1.2, 4.6, 10.0, 17.3, 23.2, 24.3, 30.6, etc.
I am trying to make predictions as to when the next 'data event' will happen. Fitting the timings against the 'data event' number doesn't produce a good fit. I was wondering if a neural network based method or any other method exists that is suitable for such analysis. Or is this a problem with the data being too chaotic and just not being predictable? I am aware that most methods get much worse/unuseable when extrapolating outside of the dataset but am hoping there is a method.