Ilya M. Sobol

A Primer for the Monte Carlo Method (eBook, ePUB)

• Format: ePub

Produktbeschreibung

The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. As a universal numerical technique, the method became possible only with the advent of computers, and its application continues to expand with each new computer generation. A Primer for the Monte Carlo Method demonstrates how practical problems in science, industry, and trade can be solved using this method. The book features the main schemes of the Monte Carlo method and presents various examples of its application, including queueing, quality and reliability estimations, neutron transport, astrophysics, and numerical analysis. The only prerequisite to using the book is an understanding of elementary calculus.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 126
• Erscheinungstermin: 24. April 2018
• Englisch
• ISBN-13: 9781351469579
• Artikelnr.: 56842521

Autorenporträt

Sobol, Ilya M.

Inhaltsangabe

Introduction: General Idea of the Method. Simulating Random Variables:
Random Variables. Generating Random Variables on a Computer.
Transformations of Random Variables. Examples of the Application of the
Monte Carlo Method: Simulation of a Mass-Servicing System. Calculating the
Quality and Reliability of Devices. Computation of Neutron Transmission
through a Plate. An Astrophysical Problem. Evaluating a Definite Integral.
Additional Information: On Pseudorandom Numbers. On Methods for Generating
Random Variables. On Monte Carlo Algorithms. References. Index

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Introduction: General Idea of the Method. Simulating Random Variables: Random Variables. Generating Random Variables on a Computer. Transformations of Random Variables. Examples of the Application of the Monte Carlo Method: Simulation of a Mass-Servicing System. Calculating the Quality and Reliability of Devices. Computation of Neutron Transmission through a Plate. An Astrophysical Problem. Evaluating a Definite Integral. Additional Information: On Pseudorandom Numbers. On Methods for Generating Random Variables. On Monte Carlo Algorithms. References. Index

Rezensionen

"...Useful and thought-provoking...readily accessible to researchers in a wide variety of fields."
Bruce Jay Collings, Brigham Young University, in the Journal of the American Statistical Association, December 1997