An Automated Multiresolution Procedure for Modeling Complex Arrival Processes

References

• Arkin B. L., Leemis L. M. Nonparametric estimation of the cumulative intensity function for a nonhomogeneous Poisson process from overlapping realizations. Management Sci. (2000) 46:989–998Link, Google Scholar
• Avramidis A. N., Wilson J. R. A flexible method for estimating inverse distribution functions in simulation experiments. ORSA J. Comput. (1994) 6:342–355Link, Google Scholar
• Çinlar E.Introduction to Stochastic Processes (1975) (Prentice-Hall, Englewood Cliffs, NJ) Google Scholar
• Draper N. R., Smith H.Applied Regression Analysis (1998) 3rd ed.(John Wiley & Sons, New York) Crossref, Google Scholar
• Johnson M. A., Lee S., Wilson J. R. Experimental evaluation of a procedure for estimating nonhomogeneous Poisson processes having cyclic behavior. ORSA J. Comput. (1994) 6:356–368Link, Google Scholar
• Kao E. P. C., Chang S.-L. Modeling time-dependent arrivals to service systems: A case in using a piecewise-polynomial rate function in a nonhomogeneous Poisson process. Management Sci. (1988) 34:1367–1379Link, Google Scholar
• Kuhl M. E. Estimation and simulation of nonhomogeneous Poisson processes having multiple periodicities. (1994) Accessed August 25, 2004M.S. thesis, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, ftp://ftp.ncsu.edu/pub/eos/pub/jwilson/kuhl94ms.pdfGoogle Scholar
• Kuhl M. E., Wilson J. R. User's manual for mp3mle and mp3sim: Software for estimating and simulating nonhomogeneous Poisson processes. (1996) Accessed August 25, 2004Department of Industrial Engineering, North Carolina State University, Raleigh, NC, ftp://ftp.ncsu.edu/pub/eos/pub/jwilson/mp3-user-man.pdfGoogle Scholar
• Kuhl M. E., Wilson J. R. Least squares estimation of nonhomogeneous Poisson processes. J. Statist. Comput. Simulation (2000) 67:75–108Crossref, Google Scholar
• Kuhl M. E., Wilson J. R. Modeling and simulating Poisson processes having trends or nontrigonometric cyclic effects. Eur. J. Oper. Res. (2001) 133:566–582Crossref, Google Scholar
• Kuhl M. E., Damerdji H., Wilson J. R., Andradóttir S., Healy K. J., Withers D. H., Nelson B. L. Estimating and simulating Poisson processes with trends or asymmetric cyclic effects. Proc. 1997 Winter Simulation Conf. (1997a) Accessed August 25, 2004(Institute of Electrical and Electronics Engineers, Piscataway, NJ) 287–295 http://www.informs-sim.org/wsc97papers/0287.PDFCrossref, Google Scholar
• Kuhl M. E., Sumant S., Wilson J. R., Chick S., Sánchez P. J., Ferrin D., Morrice D. J. A flexible automated procedure for modeling complex arrival processes. Proc. 2003 Winter Simulation Conf. (2003) Accessed August 25, 2004(Institute of Electrical and Electronics Engineers, Piscataway, NJ) 399–407 http://www.informs-sim.org/wsc03papers/049.pdfCrossref, Google Scholar
• Kuhl M. E., Wilson J. R., Johnson M. A. Estimating and simulating Poisson processes having trends or multiple periodicities. IIE Trans. (1997b) 29:201–211Crossref, Google Scholar
• Lee S., Wilson J. R., Crawford M. M. Modeling and simulation of a nonhomogeneous Poisson process having cyclic behavior. Comm. Statist.—Simulation (1991) 20:777–809Crossref, Google Scholar
• Leemis L. M. Nonparametric estimation of the cumulative intensity function for a nonhomogeneous Poisson process. Management Sci. (1991) 37:886–900Link, Google Scholar
• Leemis L. M. Nonparametric estimation and variate generation for a nonhomogeneous Poisson process from event count data. IIE Trans. (2004) 36:1155–1160Crossref, Google Scholar
• Lewis P. A. W. Remarks on the theory, computation, and application of the spectral analysis of series of events. J. Sound Vibration (1970) 12:353–375Crossref, Google Scholar
• Lewis P. A. W., Shedler G. S. Statistical analysis of non-stationary series of events in a data base system. IBM J. Res. Develop. (1976) 20:465–482Crossref, Google Scholar
• Massey W. A., Parker G. A., Whitt W. Estimating the parameters of a nonhomogeneous Poisson process with linear rate. Telecomm. Systems (1996) 5:361–388Crossref, Google Scholar
• Pritsker A. A. B. Life and death decisions: Organ transplantation allocation policy analysis. OR/MS Today (1998) 25:22–28Google Scholar
• Pritsker A. A. B., Martin D. L., Reust J. S., Wagner M. A. F., Daily O. P., Harper A. M., Edwards E. B., Bennett L. E., Wilson J. R., Kuhl M. E., Roberts J. P., Allen M. D., Burdick J. F., Alexopoulos C., Kang K., Lilegdon W. R., Goldsman D. Organ transplantation policy evaluation. Proc. 1995 Winter Simulation Conf. (1995) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 1314–1323Google Scholar
• Seber G. A. F.Linear Regression Analysis (1977) (John Wiley & Sons, New York) Google Scholar
• Serfling R. J.Approximation Theorems of Mathematical Statistics (1980) (John Wiley & Sons, New York) Crossref, Google Scholar
• Sumant S. G. An automated procedure for simulating complex arrival processes: A web-based approach. (2003) Accessed August 25, 2004M.S.I.E. thesis, Department of Industrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY, ftp://ftp.ncsu.edu/pub/eos/pub/jwilson/sumant03ms.pdfGoogle Scholar