the practical problem is as follows:
- There are several objects, say, 20 volcanos, that erupt at some point of time (event occurs).
- Every volcano has it's unique distribution of 'waiting time' until next eruption (event) occurs.
- Every volcano has some observations (from 15 to 60) on those waiting times until next event.
- There's no other events (like, only eruption can occur, nothing more), and every volcano has, basically, no failures (it should erupt sooner or later).
What is the proper framework or analysis toolkit for those type of data? I considered time-series techniques, because those events take place for every object in ordered manner like so: ...waiting time>event>waiting time>event>waiting time... But time series analysis implies, that every observation should take place in equal-spaced timing. And my volcano #1 erupt, say 19.07.2017 18:30:00 and nothing happens until 01.08.2017 02:46:00. Or survival analysis tools are more proper here? Particularly, I'm interested in predicting those eruptions and I'm trying to find most useful covariates for it.
Is survival analysis suitable for it?