DocumentCode
2163944
Title
Dependence modeling for stochastic simulation
Author
Biller, Bahar ; Ghosh, Soumyadip
Author_Institution
Tepper Sch. of Bus., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume
1
fYear
2004
fDate
5-8 Dec. 2004
Lastpage
161
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2004. Proceedings of the 2004 Winter
Print_ISBN
0-7803-8786-4
Type
conf
DOI
10.1109/WSC.2004.1371312
Filename
1371312
Link To Document