Searching for authors named "Lawrence Leemis" – sorted by Relevance.
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Simulation Input Modeling
- …Discrete-event simulation models typically have stochastic components that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a close match between the input model and the true underlying probabilistic mechanism associated with the system. The genera…
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Input Modeling Techniques For Discrete-Event Simulations
- …Most discrete-event simulation models have stochastic elements that mimic the probabilistic nature of the system under consideration. A close match between the input model and the true underlying probabilistic mechanism associated with the system is required for successful input modeling. The genera…
- Cited by 4 (0 self) – Add To MetaCart
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Input Modeling
- …Discrete-event simulation models typically have stochastic elements that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a close match between the input model and the true underlying probabilistic mechanism associated with the system. The general …
- Cited by 3 (0 self) – Add To MetaCart
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Nonparametric estimation and variate generation for a nonhomogeneous Poisson process from event count data
- …Given a finite time horizon that has been partitioned into subintervals over which event counts have been accumulated for multiple realizations of a population NonHomogeneous Poisson Process (NHPP), this paper develops point and confidence-interval estimators for the cumulative intensity (or mean va…
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Variate Generation for Accelerated Life and Proportional Hazards Models
- …The accelerated life and proportional hazards lifetime models are used to account for the effects of covariates on a random lifetime. Variate generation algorithms for Monte Carlo simulation in both the renewal and nonhomogeneous Poisson process cases are a simple extension of the inverse-cdf techni…
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The Arctangent Survival Distribution
- …This paper is presented to give the UBT model a second distribution that enjoys a closed-form survivor function and has been demonstrated to adequately describe well-known data sets. Acknowledgements…
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Input Modeling Using A Computer Algebra System
- …Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit several distributions to a data set, then determine the distribution with the best fit by comparing goodness-of-fit stati…
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A Comparison of Approximate Interval
- …this paper is to compare the accuracy of two approximate confidence interval estimators for the Bernoulli parameter p. The approximate confidence intervals are based on the normal and Poisson approximations to the binomial distribution. Charts are given to indicate which approximation is appropriate…
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On the Minimum of Independent Geometrically Distributed Random Variables
- …The expectations E[X (1) ], E[Z (1) ], and E[Y (1) ] of the minimum of n independent geometric, modified geometric, or exponential random variables with matching expectations differ. We show how this is accounted for by stochastic variability and how E[X (1) ]=E[Y (1) ] equals the expected number of…
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