Regenerative Stochastic Simulation (Statistical Modeling and Decision Science)

simulation Is A Controlled Statistical Sampling Technique That Can Be Used To Study Complex Stochastic Systems When Analytic And/or Numerical Techniques Do Not Suffice. The Focus Of This Book Is On Simulations Of Discrete-event Stochastic Systems; Namely, Simulations In Which Stochastic State Transitions Occur Only At An Increasing Sequence Of Random Times. The Discussion Emphasizes Simulations On A Finite Or Countably Infinite State Space.

• Develops Probabilistic Methods For Simulation Of Discrete-event Stochastic Systems
• Emphasizes Stochastic Modeling And Estimation Procedures Based On Limit Theorems For Regenerative Stochastic Processes
• Includes Engineering Applications Of Discrete-even Simulation To Computer, Communication, Manufacturing, And Transportation Systems
• Focuses On Simulations With An Underlying Stochastic Process That Can Specified As A Generalized Semi-markov Process
• Unique Approach To Simulation, With Heavy Emphasis On Stochastic Modeling
• Includes Engineering Applications For Computer, Communication, Manufacturing, And Transportation Systems