Modeling and Computer Simulation (TOMACS)


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ACM Transactions on Modeling and Computer Simulation (TOMACS), Volume 13 Issue 3, July 2003

Modeling and generating multivariate time-series input processes using a vector autoregressive technique
Bahar Biller, Barry L. Nelson
Pages: 211-237
DOI: 10.1145/937332.937333
We present a model for representing stationary multivariate time-series input processes with marginal distributions from the Johnson translation system and an autocorrelation structure specified through some finite lag. We then describe how to...

Computing the distribution function of a conditional expectation via monte carlo: Discrete conditioning spaces
Shing-Hoi Lee, Peter W. Glynn
Pages: 238-258
DOI: 10.1145/937332.937334
We examine different ways of numerically computing the distribution function of conditional expectations where the conditioning element takes values in a finite or countably infinite outcome space. Both the conditional expectation and the...

Dynamic structure multiparadigm modeling and simulation
Fernando J. Barros
Pages: 259-275
DOI: 10.1145/937332.937335
This article presents the Heterogeneous Flow System Specification (HFSS), a formalism aimed to represent hierarchical and modular hybrid flow systems with dynamic structure. The concept of hybrid flow systems provides a generalization of the...

Behavior of the NORTA method for correlated random vector generation as the dimension increases
Soumyadip Ghosh, Shane G. Henderson
Pages: 276-294
DOI: 10.1145/937332.937336
The NORTA method is a fast general-purpose method for generating samples of a random vector with given marginal distributions and given correlation matrix. It is known that there exist marginal distributions and correlation matrices that the NORTA...