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Coverage Error for Confidence Intervals Arising in Simulation Output Analysis
Coverage Error Confidence Intervals Arising Simulation Output Analysis
2015/7/8
Coverage error asymptotics for confidence intervals arising in simulation are discussed~ Asymptotic expansions, to order O(n-1) (n is the sample size), are given for confidence intervals associated wi...
Discretization Error in Simulation of One-dimensional Reflecting Brownian Motion
Discretization Error Simulation One-dimensional Reflecting Brownian Motion
2015/7/8
This paper is concerned with various aspects of the simulation of one-dimensional reflected (or regulated) Brownian motion. The main result shows that the discretization error associated with the Eule...
Transient Simulation Via Empirically-Based Coupling
Transient Simulation Empirically-Based Coupling
2015/7/8
In this paper we consider the use of coupling ideas in efficiently computing a certain class of transient performance measures. Specifically, we consider the setting in which the stationary distributi...
Two-sided Taboo Limits for Markov Processes and Associated Perfect Simulation
Markov processes Quasi-stationary distribution Eigenvalues Perron{Frobenius theory
2015/7/8
In this paper, we study the two-sided taboo limit processes that arise when a Markov chain or process is conditioned on staying in some set A for a long period of time. The taboo limit is time-homogen...
Multivariate Standardized Time Series for Steady-State Simulation Output Analysis
Simulation statistical analysis multivariate steady-state output analysi
2015/7/8
The theory of standardized time series, initially proposed to estimate a single steady-state mean from the output of a simulation, is extended to the case where more than one steady-state mean is to b...
Regenerative Steady-State Simulation of Discrete-Event Systems
Regenerative Steady-State Simulation Discrete-Event Systems
2015/7/8
The regenerative method possesses certain asymptotic properties that dominate those of other steady-state simulation output analysis methods, such as batch means. Therefore, applying the regenerative ...
Rare-Event Simulation for Infinite Server Queues
Rare-Event Simulation Infinite Server Queues
2015/7/8
We discuss rare-event simulation methodology for computing tail probabilities for infinite-server queues. Our theoretical discussion also offers some new simulation insights into the change-of-measure...
Approximating Martingales for Variance Reduction in Markov Process Simulation
Variance reduction Markov process simulation martingale
2015/7/8
“Knowledge of either analytical or numerical approximations should enable more efficient simulation estimators to be constructed.” This principle seems intuitively plausible and certainly attractive, ...
Simulation Algorithms for Regenerative Processes
Simulation Algorithms Regenerative Processes
2015/7/6
This chapter is concerned with reviewing the basic ideas and concepts underlying the use of regenerative structure in the development of efficient simulation algorithms. While it has long been known t...
Simulation-based Response Surface Estimation in the Presence of Monotonicity
Simulation-based Response Surface Estimation Presence Monotonicity
2015/7/6
In many stochastic models, it is known that the response surface corresponding to a particular performance measure is monotone in the underlying parameter. For example, the steady-state mean waiting t...
Much of the rare-event simulation literature is concerned with the development of asymptotically optimal algorithms. Because of the difficulties associated with applying these ideas to complex models,...
A Large Deviations View of Asymptotic Efficiency for Simulation Estimators
Large Deviations View Asymptotic Efficiency Simulation Estimators
2015/7/6
Consider a simulation estimator α(c) based on expending c units of computer time, to estimate a quantity α. One measure of efficiency is to attempt to minimize P(|α(c)−α|>ε) for large c. This he...
Efficient Rare-event Simulation for the Maximum of Heavy-tailed Random Walks
State-dependent importance sampling rare-event simulation heavy-tails Lyapunov bounds random walks
2015/7/6
Let (Xn: n ≥ 0) be a sequence of i.i.d. r.v.’s with negative mean. Set S0 = 0 and define Sn = X1 +· · ·+Xn. We propose an importance sampling algorithm to estimate the tail of M = max{Sn: n ≥ 0} that ...
Rare Event Simulation for a Generalized Hawkes Process
Rare Event Simulation Generalized Hawkes Process
2015/7/6
In this paper we study rare event simulation for the tail probability of an affine point process (Jt)t≥0 that generalizes the Hawkes process. By constructing a suitable exponential martingale, we are ...
How to Deal with the Curse of Dimensionality of Likelihood Ratios in Monte Carlo Simulation
Cross-entropy Rare-event probability estimation Screening Simulation
2015/7/6
In this work we show how to resolve, at least partially, the curse of dimensionality of likelihood ratios (LRs) while using importance sampling (IS) to estimate the performance of high-dimensional Mon...