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Hands-On Simulation Modeling with Python

You're reading from  Hands-On Simulation Modeling with Python

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781838985097
Pages 346 pages
Edition 1st Edition
Languages
Author (1):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro

Table of Contents (16) Chapters

Preface 1. Section 1: Getting Started with Numerical Simulation
2. Chapter 1: Introducing Simulation Models 3. Chapter 2: Understanding Randomness and Random Numbers 4. Chapter 3: Probability and Data Generation Processes 5. Section 2: Simulation Modeling Algorithms and Techniques
6. Chapter 4: Exploring Monte Carlo Simulations 7. Chapter 5: Simulation-Based Markov Decision Processes 8. Chapter 6: Resampling Methods 9. Chapter 7: Using Simulation to Improve and Optimize Systems 10. Section 3: Real-World Applications
11. Chapter 8: Using Simulation Models for Financial Engineering 12. Chapter 9: Simulating Physical Phenomena Using Neural Networks 13. Chapter 10: Modeling and Simulation for Project Management 14. Chapter 11: What's Next? 15. Other Books You May Enjoy

Technical requirements

In this chapter, we will address resampling method technologies. In order to deal with the topics in this chapter, it is necessary that you have a basic knowledge of algebra and mathematical modeling. To work with the Python code in this chapter, you'll need the following files (available on GitHub at the following URL: https://github.com/PacktPublishing/Hands-On-Simulation-Modeling-with-Python):

  • JackknifeEstimator.py
  • BootstrapEstimator.py
  • KfoldCrossValidation.py
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