I've got data representing a sequence of events at irregular intervals and an outcome. There are a fixed number of event types, about 10 of them. The outcome being modeled is binary.
Arguably the following are important to incorporate into the model:
1) Which events occur
2) The order in which the events occur
3) The time lag between events
I.e: User has event A at start, 5 months later event C, and outcome is positive. Another user has event B at start, 3 days later event A, 2 days later event D, and outcome is no.
I've also got some static (non sequence data) for each user which I'd like to incorporate.
What is the best approach to model this?
Thanks in advance.