I need to answer the following question:
What is the probability that the event 1 will occur at some point in the time for a new sample? At which time point is this more likely to occur?
1: event occurred at a specific time point, 0: event did not occur, -1: the opposite of the requested event occurred (also not interesting).
For each sample, 6 time points are measured over time. Let us assume this is for example every week (1w, 2w, 3w, 4w, 5w, 6w).
sample 1 = (0, 0, 0, 0, 0, 1)
sample 2 = (0, 0, 1, 1, 1, 1)
sample 3 = (0, 0, 0, 0, 1, 1)
sample 4 = (0, 0, 0, 0, 0, 1)
sample 5 = (0, 0, 0, 1, 1, 1)
sample 6 = (0, 0, 0, 0, 0, 1)
sample 7 = (0, -1, -1, -1, -1, 0)
sample 8 = (0, 0, 0, 0, 0, 0)
What model would be appropriate for this?
Apparently, there are also "noisy" samples where we do not observe the event (samples 7, 8).