Multivariate statistical simulation
Multivariate statistical simulation
Simulation methodology for statisticians, operations analysts, and engineers: vol. 1
Simulation methodology for statisticians, operations analysts, and engineers: vol. 1
Curves and surfaces for computer aided geometric design
Curves and surfaces for computer aided geometric design
The TES methodology: modeling empirical stationary time series
WSC '92 Proceedings of the 24th conference on Winter simulation
Using bivariate Be´zier distributions to model simulation input processes
WSC '94 Proceedings of the 26th conference on Winter simulation
Organ transplantation policy evaluation
WSC '95 Proceedings of the 27th conference on Winter simulation
Using univariate Be´zier distributions to model simulation input processes
WSC '93 Proceedings of the 25th conference on Winter simulation
Elementary Numerical Analysis: An Algorithmic Approach
Elementary Numerical Analysis: An Algorithmic Approach
Recent developments in input modeling with Bézier distributions
WSC '96 Proceedings of the 28th conference on Winter simulation
Multivariate input modeling with Johnson distributions
WSC '96 Proceedings of the 28th conference on Winter simulation
Modeling dependencies in stochastic simulation inputs
Proceedings of the 29th conference on Winter simulation
Input modeling tools for complex problems
Proceedings of the 30th conference on Winter simulation
Advanced input modeling for simulation experimentation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Steps to implement Bayesian input distribution selection
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Bayesian methods: bayesian methods for simulation
Proceedings of the 32nd conference on Winter simulation
Proceedings of the 32nd conference on Winter simulation
Resampling methods for input modeling
Proceedings of the 33nd conference on Winter simulation
Introduction to modeling and generating probabilistic input processes for simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Introduction to modeling and generating probabilistic input processes for simulation
Proceedings of the 38th conference on Winter simulation
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A graphical interactive technique for modeling bivariate simulation inputs is based on a family of continuous univariate and bivariate probability distributions with bounded support that are described by Be´zier curves and surfaces, respectively. This family of distributions has a natural, extensible parameterization so that all parameters have a meaningful interpretation; and the complete family is capable of accurately representing an unlimited variety of shapes for marginal distributions together with many common types of bivariate stochastic dependence. This approach to simulation input modeling is implemented in a Windows-based software system called PRIME-PRobabilistic Input Modeling Environment. Several examples illustrate the application of PRIME to subjective and data-driven estimation of bivariate distributions representing simulation inputs.