TITLE:
The Conditional Poisson Process and the Erlang and Negative Binomial Distributions
AUTHORS:
Anurag Agarwal, Peter Bajorski, David L. Farnsworth, James E. Marengo, Wei Qian
KEYWORDS:
Conditional Distribution, Hierarchical Model, Mixture Distribution, Poisson Process, Stochastic Process
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.1,
February
9,
2017
ABSTRACT: It is a well known fact that for the hierarchical model of a Poisson random variable Ywhose mean has an Erlang distribution, the unconditional distribution of Y is negative binomial. However, the proofs in the literature [1] [2] provide no intuitive understanding as to why this result should be true. It is the purpose of this manuscript to give a new proof of this result which provides such an understanding. The memoryless property of the exponential distribution allows one to conclude that the events in two independent Poisson processes may be regarded as Bernoulli trials, and this fact is used to achieve the research purpose. Another goal of this manuscript is to give another proof of this last fact which does not rely on the memoryless property.