The gamma Poisson distribution combines two probability distributions to model counts in non-homogeneous time series. It uses a Poisson distribution to count events occurring in random time intervals, which are themselves governed by a gamma distribution. This distribution captures variability in both the number of events and the time intervals between them, making it suitable for analyzing data where the intensity of events varies over time, such as in reliability engineering and queuing systems.
