I have a time-series of noisy data which occasionally triggers an event, and once that happens, the noise calms down and the cycle repeats itself (until the event is triggered once again). What I want to try and model is essentially the likelihood of the event occurring at any point throughout my univariate time series.
For example, in the picture below, the blue line measures the time to event, with the red line being the actual data. How could I predict when the blue line dips/the event occurs?
I thought Survival analysis would fit the bill, as it deals with modelling time to events, but I have had difficulty locating the right resources, and would appreciate any advice.