Simulating Multivariate Nonhomogeneous Poisson Processes Using Projections

  • Authors:
  • Evan A. Saltzman;John H. Drew;Lawrence M. Leemis;Shane G. Henderson

  • Affiliations:
  • RAND Corporation;The College of William & Mary;The College of William & Mary;Cornell University

  • Venue:
  • ACM Transactions on Modeling and Computer Simulation (TOMACS)
  • Year:
  • 2012

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Abstract

Established techniques for generating an instance of a multivariate NonHomogeneous Poisson Process (NHPP) such as thinning can become highly inefficient as the dimensionality of the process is increased, particularly if the defining intensity (or rate) function has a pronounced peak. To overcome this inefficiency, we propose an alternative approach where one first generates a projection of the NHPP onto a lower-dimensional space, and then extends the generated points to points in the original space by generating from appropriate conditional distributions. One version of this algorithm replaces a high-dimensional problem with a series of one-dimensional problems. Several examples are presented.