Synopses & Reviews
Ross's
Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes.
This text explains how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. It presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model.
New to this Edition:
-More focus on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis
-A chapter on Markov chain monte carlo methods with many examples
-Unique material on the alias method for generating discrete random variables
Review
“...It is outstanding because it is what it is and no other textbook out there does this job.”
- Kris Ostaszewski, Illinois State University
“Examples are infinitely more interesting than in almost any other book! Ross always explains clearly, I especially enjoy the exposition of the brand new sections” - Matt Carlton, Cal Polytechnic Institute
Review
Applied examples illustrate the theory and motivate the student
Review
b."
- Kris Ostaszewski, Illinois State University
"Examples are infinitely more interesting than in almost any other book! Ross always explains clearly, I especially enjoy the exposition of the brand new sections" - Matt Carlton, Cal Polytechnic Institute
Synopsis
This text explains how to generate random variables which shows how to analyze a model by use of a simulation study. It shows how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. Presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model.
Ross's writing style. He gives the words
personality and makes the material interesting and
lively.
Presents the statistics needed to analyze simulated
data as well as that needed for validating the
simulation model.
Applied examples are integrated throughout the text
to illustrate the theory and motivate the student,
such as multiple server queuing methods, inventory
control, and exercising stock options.
Synopsis
Now updated, Ross's text introduces aspiring and practicing actuaries, engineers, computer scientists, and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes.
About the Author
Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal
Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.
University of Southern California, Los Angeles, USA
Table of Contents
Preface; Introduction; Elements of Probability;
Random Numbers; Generating Discrete Random Variables; Generating Continuous Random Variables; The Discrete Event Simulation Approach; Statistical Analysis of Simulated Data; Variance Reduction Techniques; Statistical Validation Techniques; Markov Chain Monte Carlo Methods; Some Additional Topics; Exercises; References; Index