We're still working on our article for Monte Carlo Method. Please check back soon for more information.
3ox3w4|
Find a path to becoming a Monte Carlo Method. Learn more at:
OpenCourser.com/topic/3ox3w4/monte
Reading list
We've selected 19 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Monte Carlo Method.
A comprehensive textbook on Bayesian data analysis that uses Markov chain Monte Carlo methods.
Provides a detailed overview of Monte Carlo methods, specifically in the context of financial engineering. The book focuses on a variety of topics relevant to this field, including option pricing, risk management, and stochastic processes.
This paper is one of the most influential papers in the history of computational physics. The authors introduce the Monte Carlo method to the field of quantum mechanics, providing a new tool for solving complex quantum systems.
Reference guide for Markov chain Monte Carlo methods, with computer programs and examples.
Comprehensive reference guide on Monte Carlo simulation and its applications in finance.
Comprehensive textbook on Monte Carlo methods.
Covers quadrature methods such as the Monte Carlo method and quasi-Monte Carlo methods.
Comprehensive reference guide on quasi-Monte Carlo methods with a focus on applications in computational finance and numerical integration.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on statistical applications. The authors present a wide range of topics, including Markov chain Monte Carlo, importance sampling, and Bayesian inference. The book is suitable for both beginners and experienced researchers.
A detailed account of numerical methods in finance, including Monte Carlo methods.
Textbook on Monte Carlo methods and simulation.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in statistical physics. The authors cover a wide range of topics, including phase transitions, critical phenomena, and transport properties.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in computational finance. The author covers a wide range of topics, including option pricing, risk management, and portfolio optimization.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in simulation and optimization. The author covers a wide range of topics, including random number generation, variance reduction techniques, and Markov chain Monte Carlo.
Provides a detailed overview of Monte Carlo methods, specifically in the context of climate modeling. The book focuses on a variety of topics relevant to this field, including climate sensitivity, extreme events, and climate projections.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in polymer science. The authors cover a wide range of topics, including polymer simulations, phase transitions, and transport properties.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in applied statistics. The authors cover a wide range of topics, including Bayesian inference, missing data imputation, and sensitivity analysis.
Provides a comprehensive overview of Monte Carlo methods, with a particular focus on applications in systems biology. The author covers a wide range of topics, including stochastic modeling, parameter estimation, and network inference.
E. Handschin provides a gentle introduction to Monte Carlo methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/3ox3w4/monte
Save
