Abstract
Computer simulation models often include one or more variables that play important roles in the model. Some of the random variables are of the continuous type and others are discrete. The analyst is confronted with choosing the proper probability distribution for each variable, and also with estimating the associated parameter(s) value. The chapter describes some of the common ways to select the distribution and to estimate the associated parameter values when some empirical or sample data is available from the real system.
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References
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Zanakis, S.H.: A simulation study of some simple estimators for the three-paramater Weibull distribtuion. J. Stat. Comput. Simul. 9, 101–116 (1979)
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Thomopoulos, N.T. (2013). Choosing the Probability Distribution from Data. In: Essentials of Monte Carlo Simulation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6022-0_10
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DOI: https://doi.org/10.1007/978-1-4614-6022-0_10
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6021-3
Online ISBN: 978-1-4614-6022-0
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