I'm examining the activity of customers over the years which have about one event per year. This results is many short time-series for which I found the distributions (hit/miss over 4 years sorted by probability in the data):0000 : 0.318340001 : 0.175820010 : 0.136050100 : 0.135541000 : 0.128860011 : 0.017171100 : 0.016500110 : 0.015780101 : 0.012201010 : 0.011171001 : 0.008830111 : 0.005711110 : 0.005651111 : 0.004961101 : 0.003841011 : 0.00351Apparently a purely uncorrelated binomial model wouldn't do, but one can observe that if both, the number of 1's and 11's coincide, then the probabilities are approximately equal (apart from a small recency effect of 0001).Can you see a way to approach such data to deduce a probabilistic model? Basically where I have only a few probability parameters which roughly explain this distribution?
How to find a model for a short discrete time-series?
time series