Random number generation and Monte Carlo methods

Bibliographic Information

Random number generation and Monte Carlo methods

James E. Gentle

(Statistics and computing)

Springer, c1998

Available at  / 41 libraries

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Note

Includes bibliographical references (p. 205-235) and indexes

Description and Table of Contents

Description

This text surveys techniques of random number generation and the use of random numbers in Monte Carlo simulation. It covers basic principles, as well as methods such as parallel random number generation, nonlinear congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo. Methods for generating random variates from the standard distributions are presented, but also general techniques useful in more complicated models and in novel settings are described. The emphasis throughout the book is on practical methods that work well in late-1990s computing environments. The book includes exercises and can be used as a test or supplementary text for various courses in modern statistics. It could serve as the primary test for a specialized course in statistical computing, or as a supplementary text for a course in computations statistics and other areas of modern statistics that rely on simulation. The book, which covers recent developments in the field, could also serve as a useful reference for practitioners.

Table of Contents

  • Simulating random numbers from a uniform distribution
  • transformations of uniform deviates
  • simulating random numbers from nonuniform distributions
  • generation of random samples and permutations
  • Monte Carlo methods
  • quality of random number generators
  • software for random number generation
  • Monte Carlo studies in statistics.

by "Nielsen BookData"

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