Simulation Methods for Poisson Processes in Nonstationary Systems
Lewis, Peter A.W.
Shedler, Gerald S.
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The nonhomogeneous Poisson process is a widely used model for a series of events (stochastic point process) in which the "rate" or "intensity" of occurrence of points varies, usually with time. The process has the characteristic properties that the number of points in any finite set of nonoverlapping intervals are mutually independent random variables, and that the number of points in any of these intervals has a Poisson distribution. In this paper we first discuss several general methods for simulation of one-dimension non-homogeneous Poisson process; these include time-scale transformation of a homogeneous (rate one) Poisson process via the inverse of the integrated rate function, generation of the individual intervals between points, and generation of a Poisson number of order statistics from a fixed density function.
Winter Simulation Conference
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