Simulation and the Monte Carlo Method

Contents

1. Systems, Models, Simulation and the Monte Carlo Method

2. Random Number Generation

3. Random Variate Generation

4. Monte Carlo Integration and Variance Reduction Techniques

5. Linear Equations and Markov Chains

6. Regenerative Method for Simulation Analysis

7. Monte Carlo Optimization

This is a classic introduction to the Monte Carlo method. It starts with basic concepts. It illustrates techniques for generating pseudorandom numbers and pseudorandom variates. The discussions of variance reduction techniques are clear and very accessible. The book closes with discussions of some more specialized topics.

This book is perfect for a quantitatively oriented professional who has some intuitive familiarity with the Monte Carlo method but wants to achieve more formal understanding so they can implement variance reduction techniques in their Monte Carlo analyses.

 

For related books, see sections:

Mathematics - Monte Carlo Method

Financial Engineering - Numerical Methods

 

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