Name
Abstract | ||
|---|---|---|
Techniques are presented for modeling and generating the univariate and multivariate probabilistic input processes that drive many simulation experiments. Among univariate input models, emphasis is given to the generalized beta distri- bution family, the Johnson translation system of distribu- tions, and the Bézier distribution family. Among bivariate and higher-dimensional input models, emphasis is given to computationally tractable extensions of univariate Johnson distributions. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Poisson processes. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1162708.1162720 | Winter Simulation Conference |
Keywords | DocType | ISBN |
multivariate probabilistic input process,higher-dimensional input model,univariate input model,simulation experiment,nonparametric technique,nonhomogeneous Poisson,Johnson translation system,zier distribution family,generalized beta distribution family,univariate Johnson distribution | Conference | 0-7803-9519-0 |
Citations | PageRank | References |
16 | 1.25 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emily K. Lada | 1 | 189 | 20.59 |
| Mary Ann Flanigan Wagner | 2 | 116 | 20.35 |
| Natalie M. Steiger | 3 | 247 | 23.94 |
| James R. Wilson | 4 | 840 | 143.42 |