• Publications
  • Influence
Principles of Discrete Event Simulation
  • 524
  • 36
A Comparison of Four Monte Carlo Methods for Estimating the Probability of s-t Connectedness
  • G. S. Fishman
  • Computer Science
  • IEEE Transactions on Reliability
  • 1 June 1986
This paper describes and compares the performance of four alternative Monte Carlo sampling plans for estimating the probability that two nodes, s and t, are connected in an undirected network whose arcs fail randomly and independently. Expand
  • 142
  • 17
Discrete-Event Simulation : Modeling, Programming, and Analysis
Preface.- Simulation in Perspective.- Modeling Concepts Data Collection and Averages. Expand
  • 333
  • 15
Grouping Observations in Digital Simulation
This paper presents a method for deriving a confidence interval for a population mean from the output of a simulation run. The method groups the observations on a run into batches and uses theseExpand
  • 183
  • 15
An Implementation of the Batch Means Method
This article introduces the LBATCH and ABATCH rules for applying the batch means method to analyze output of Monte Carlo and, in particular, discrete-event simulation experiments. Expand
  • 110
  • 14
A Monte Carlo Sampling Plan for Estimating Network Reliability
We present a general class of Monte Carlo sampling plans for estimating g = gs, T, the probability that a specified node s is connected to all nodes in a node set T in an undirected network whose arcs are subject to random failure. Expand
  • 156
  • 13
Concepts and Methods in Discrete Event Digital Simulation
  • 415
  • 11
Discrete-event simulation
This book describes the fundamentals of discrete-event simulation from the perspective of highly interactive PC and workstation environments. Expand
  • 333
  • 10
Bias Considerations in Simulation Experiments
  • G. S. Fishman
  • Mathematics, Computer Science
  • Oper. Res.
  • 1 August 1972
A first-order autoregressive scheme to investigate the effects of initial conditions in a simulation on the estimation of the population mean of a process of interest. Expand
  • 72
  • 8
Spectral Methods in Econometrics.
  • 108
  • 8