Title :
Dependence modeling for stochastic simulation
Author :
Biller, Bahar ; Ghosh, Soumyadip
Author_Institution :
Tepper Sch. of Bus., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
An important step in designing stochastic simulation is modeling the uncertainty in the input environment of the system being studied. Obtaining a reasonable representation of this uncertainty can be challenging in the presence of dependencies in the input process. This tutorial attempts to provide a coherent narrative of the central principles that underlie methods that aim to model and sample a wide variety of dependent input processes.
Keywords :
digital simulation; probability; random processes; stochastic processes; dependence model; stochastic simulation design; uncertainty model; univariate probability distributions; Autocorrelation; Computer networks; Manufacturing systems; Probability distribution; Random variables; Software packages; Stochastic processes; Stochastic systems; Uncertainty; Video compression;
Conference_Titel :
Simulation Conference, 2004. Proceedings of the 2004 Winter
Print_ISBN :
0-7803-8786-4
DOI :
10.1109/WSC.2004.1371312
