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Random Number Generation and Monte Carlo Methods Book

Random Number Generation and Monte Carlo Methods
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Random Number Generation and Monte Carlo Methods, Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These pseudorandom numbers must pass statistical tests just as random samples, Random Number Generation and Monte Carlo Methods
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  • Random Number Generation and Monte Carlo Methods
  • Written by author James E. Gentle
  • Published by Springer-Verlag New York, LLC, July 01, 2003
  • Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These "pseudorandom" numbers must pass statistical tests just as random samples
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Book Categories

Authors

Simulating Random Numbers from a Uniform Distribution
• Quality of Random Number Generation
• Quasirandom Numbers
• Transformations of Uniform Deviates: General Methods
• Simulating Random Numbers from Specific Distributions
• Generation of Random Samples, Permutations, and Shastic Processes
• Monte Carlo Methods
• Software for Random Number Generation
• Monte Carlo Studies in Statistics


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Random Number Generation and Monte Carlo Methods, Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These pseudorandom numbers must pass statistical tests just as random samples, Random Number Generation and Monte Carlo Methods

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Random Number Generation and Monte Carlo Methods, Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These pseudorandom numbers must pass statistical tests just as random samples, Random Number Generation and Monte Carlo Methods

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Random Number Generation and Monte Carlo Methods, Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These pseudorandom numbers must pass statistical tests just as random samples, Random Number Generation and Monte Carlo Methods

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