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Simulation Methodology for Statisticians, Operations Analysts, and Engineers. Vol. 1
 
 
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Simulation Methodology for Statisticians, Operations Analysts, and Engineers. Vol. 1 (Library Binding)

by P. W. A. Lewis (Author), Ed McKenzie (Author) "We discuss here briefly the definition and scope of simulation and its several aspects..." (more)
Key Phrases: probability integral transform method, complete jackknife, inverse probability integral transform, New York, Monte Carlo, Journal of the American Statistical Association (more...)
5.0 out of 5 stars See all reviews (1 customer review)

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Product Description
Students of statistics, operations research, and engineering will be informed of simulation methodology for problems in both mathematical statistics and systems simulation. This discussion presents many of the necessary statistical and graphical techniques.A discussion of statistical methods based on graphical techniques and exploratory data is among the highlights of Simulation Methodology for Statisticians, Operations Analysts, and Engineers.For students who only have a minimal background in statistics and probability theory, the first five chapters provide an introduction to simulation.

Product Details

  • Library Binding: 375 pages
  • Publisher: Chapman & Hall/CRC; 1 edition (December 1, 1988)
  • Language: English
  • ISBN-10: 0534094503
  • ISBN-13: 978-0534094508
  • Product Dimensions: 9.8 x 7.3 x 0.9 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
  • Amazon.com Sales Rank: #1,025,857 in Books (See Bestsellers in Books)

Inside This Book (learn more)
First Sentence:
We discuss here briefly the definition and scope of simulation and its several aspects. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
probability integral transform method, complete jackknife, inverse probability integral transform, antithetic estimate, jackknifed estimator, skewed service, using common random numbers, maximal cycle length, exponential pair, inverse probability method, crude simulation, estimated kurtosis, uniform marginal distribution, bivariate pairs, bivariate random variables, software supplement, random variable generation, conditional estimator, bias elimination, bivariate histogram, multiplicative congruential generator, bivariate exponential distribution, kurtosis estimates, nth customer, antithetic pairs
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Monte Carlo, Journal of the American Statistical Association, Annals of Mathematical Statistics, Naval Postgraduate School, Princeton University Press, Theory of Statistics, Practical Nonparametric Statistics, Journal of the Royal Statistical Society, Probability Models, The Art of Computer Programming, Value of the Moment Estimator Figure, Winter Simulation Conference, Academic Press, Annals of Statistics, Management Science, Pacific Grove, Proof See Knuth, Rand Corporation, Robust Estimates of Location, Statistical Computing, Continuous Example, Continuous Univariate Distributions, Desired Confidence Level, Discrete Example
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2 of 3 people found the following review helpful:
5.0 out of 5 stars A bible in simulation, April 5, 2000
By Alejandro C. Frery (Maceió, AL, Brazil) - See all my reviews
This books is extremely useful for those interested in using stochastic simulation, more than to those that work with the theoretical aspects of the subject. It is a well organized collection of techniques and results, with useful examples and illuminating ideas.
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