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Advanced input modeling for simulation experimentation
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Generating "dependent" quasi-random numbers
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Advanced input modeling: parameter estimation for ARTA processes
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Generating correlated matrix exponential random variables
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Dependence modeling for stochastic simulation
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Introduction to modeling and generating probabilistic input processes for simulation
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Introduction to modeling and generating probabilistic input processes for simulation
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Copula-Based Multivariate Input Models for Stochastic Simulation
Operations Research
Generating correlated matrix exponential random variables
Advances in Engineering Software
An Algorithm for Fast Generation of Bivariate Poisson Random Vectors
INFORMS Journal on Computing
Testing large scale streaming internet applications over wireless LANs
HASE'04 Proceedings of the Eighth IEEE international conference on High assurance systems engineering
Winter Simulation Conference
Correlated phase-type distributed random numbers as input models for simulations
Performance Evaluation
A study on transformation of self-similar processes with arbitrary marginal distributions
ACSAC'06 Proceedings of the 11th Asia-Pacific conference on Advances in Computer Systems Architecture
Simulating stochastic processes with OMNeT++
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ProFiDo – a toolkit for fitting input models
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INFORMS Journal on Computing
Simulation on demand for pricing many securities
Proceedings of the Winter Simulation Conference
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An ARTA (AutoRegressive-to-Anything)Process is a time series with arbitrary marginal distribution and autocorrelation structure specified through finite lag p. We develop an efficient numerical method forfitting ARTA processes and discuss its implementation in the software ARTAFACTS. We also present the software ARTAGEN that generates observations from ARTA processes for use as inputs to a computer simulation. We illustrate the use of the software with a real-world example.