I have a collection of Poisson processes each with an unknown $\lambda$.
I would like to estimate $\lambda$ for each process.
for each process I could take either the total number of event over the total time or the inverse of the mean of the waiting times.
Given that the dataset is quite small, with many of the processes having less than 5 total events, is is better to use the estimate based on the waiting times or the total count?
The replies to this question suggest that the count over the time is the best estimator, but no mention of the waiting times.