The statistical model for urban radio propagation has been proposed to describe the characteristic of radio pulse propagation in urban area. A modified Poisson process was used to model the clustering phenomena of the pulse arrival time sequence. In this paper, the model analysis is extended for more flexibility in data fitting, and generalized using a Markov chain to get a clear view of the statistical model. Some numerical results are shown for different values of the clustering parameter (Δ). Referring to the numerical results, the effect of Δ and the another clustering parameter (K) on the pulse number distribution is discussed. Next, the relation between the empirical pulse occupancy rate and the underlying occupancy rate of the model is derived for Δ1 using a Markov chain. By this extension and generalization, the statistical model of the pulse arrival times will be applied to a wide range of the clustering phenomena.