Rare Event Simulation using Monte Carlo Methods - Hardcover

Hardcover

ISBN 10: 0470772697 ISBN 13: 9780470772690

Publisher: Wiley, 2009

Synopsis

Rare Event Simulation

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue.

Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics.

Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.

About this title

About the Author

Gerardo Rubino, Research Director, the Institute of Computer Science and Random Systems Research (INRIA) INRIA Rennes - Bretagne Atlantique Research Centre Campus universitaire de Beaulieu.

Bruno Tuffin, Research Associate, the INRIA IRISA/INRIA.

From the Back Cover

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue.

Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics.

Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.

From the Inside Flap

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue.

Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics.

Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.

Edition details

• Publisher: Wiley
• Publication date: 2009
• Language: English
• ISBN 10: 0470772697
• ISBN 13: 9780470772690
• Binding: Hardcover
• Edition number: 1
• Number of pages: 284
• Editor: Rubino Gerardo