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Monte Carlo Integration with MATLAB and Simulink.

Presents detailed guidance on Monte Carlo integration methods for complex applications Monte Carlo integration has become an indispensable computational tool across science, engineering, mathematics, and economics, offering effective solutions where traditional numerical integration methods fall sho...

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Bibliographic Details
Main Author: Giordano, Arthur A.
Format: eBook
Language:English
Published: Newark : John Wiley & Sons, Incorporated, 2026.
Edition:1st ed.
Subjects:
Monte Carlo method.
Numerical integration.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Cover
  • Title Page
  • Copyright
  • Contents
  • Preface
  • Acknowledgments
  • About the Software
  • Abbreviations and Acronyms
  • List of MATLAB® and Simulink® Programs
  • About the Companion Website
  • Chapter 1 Monte Carlo and Numerical Integration Methods
  • Chapter 2 Numerical Integration
  • 2.1 Multiple Numerical Integration Methods: Evaluate I&equals
  • ∫abf(x)dx
  • 2.1.1 General Formula
  • 2.1.2 Rectangular Method
  • 2.1.3 Trapezoidal Method
  • 2.1.4 Simpson Method
  • 2.1.5 MATLAB® Program Method Integral
  • 2.2 Numerical Integration with Gauss Quadrature: Evaluate I&equals
  • ∫01x3dx
  • Estimates from rand in mcx3
  • Summary
  • 4.2 Monte Carlo Integration of a Function I&equals
  • ∫abf(x)dx, X Is an r.v. and f(x) &equals
  • x exp(−x)
  • 4.3 Investigation of Integral I&equals
  • ∫abf(x)dx Function f(x) &equals
  • x3 exp(−x) with X Having pdf U(a, b)
  • 4.3.1 MATLAB Program-mcrandsum Uniform pdf Evaluate I &equals
  • ∫abx3exp(−x)dx
  • Problems
  • Chapter 5 Monte Carlo Integration: A Binary Choice
  • 5.1 Hit-or-Miss Sampling
  • 5.1.1 Bound on the Error I−I^HMhttps://cse.engineering.nyu.edu/. K. Ming Leung (2000) has another description of this error.