In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of the ExpertFit distribution-fitting software. We use a set of real-world data to demonstrate how the software automatically specifies and ranks probability distributions, and then tells the analyst whether the “best ” candidate distribution is actually a good representation of the data. If no distribution provides a good fit, then ExpertFit can define an empirical distribution. In either case, the selected distribution is put into the proper format fo...
Many simulation practitioners can get more from their analyses by using the statistical theory on de...
International audienceSimulation approaches to inference have gained prominence in statistics educat...
Many simulation models include elements of human decision making which present some difficulty to th...
Input data modeling is a critical component of a successful simulation application. A perspective of...
An important, but often neglected, part of any sound simulation study is that of modeling each sourc...
Simulation modeling is a tool commonly used in support of intelligent decision making by senior mana...
Input analysis which involves a large amount of statistical analysis is one of the major steps in si...
This paper gives a survey on how to validate simulation models through the application of mathematic...
In this tutorial we present techniques for building valid and credible simulation models. Ideas to b...
In this tutorial we present techniques for building valid and credible simulation models. Ideas to b...
Most companies nowadays employ experts who work in tandem with a numerical forecasting system to imp...
Most companies nowadays employ experts who work in tandem with a numerical forecasting system to imp...
This paper shows which statistical techniques can be used to validate simulation models, depending o...
The steps of the process for conducting a simulation modeling and analysis project include: problem ...
Stochastic simulation models are used to predict the behavior of real systems whose components have ...
Many simulation practitioners can get more from their analyses by using the statistical theory on de...
International audienceSimulation approaches to inference have gained prominence in statistics educat...
Many simulation models include elements of human decision making which present some difficulty to th...
Input data modeling is a critical component of a successful simulation application. A perspective of...
An important, but often neglected, part of any sound simulation study is that of modeling each sourc...
Simulation modeling is a tool commonly used in support of intelligent decision making by senior mana...
Input analysis which involves a large amount of statistical analysis is one of the major steps in si...
This paper gives a survey on how to validate simulation models through the application of mathematic...
In this tutorial we present techniques for building valid and credible simulation models. Ideas to b...
In this tutorial we present techniques for building valid and credible simulation models. Ideas to b...
Most companies nowadays employ experts who work in tandem with a numerical forecasting system to imp...
Most companies nowadays employ experts who work in tandem with a numerical forecasting system to imp...
This paper shows which statistical techniques can be used to validate simulation models, depending o...
The steps of the process for conducting a simulation modeling and analysis project include: problem ...
Stochastic simulation models are used to predict the behavior of real systems whose components have ...
Many simulation practitioners can get more from their analyses by using the statistical theory on de...
International audienceSimulation approaches to inference have gained prominence in statistics educat...
Many simulation models include elements of human decision making which present some difficulty to th...