{"product_id":"rare-event-simulation-using-monte-carlo-methods-isbn-9780470772690","title":"Rare Event Simulation using Monte Carlo Methods","description":"\u003cb\u003eRare Event Simulation\u003c\/b\u003e \u003cp\u003eIn 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.  \u003c\/p\u003e\u003cp\u003eMonte 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.  \u003c\/p\u003e\u003cp\u003eGraduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.  \u003cb\u003eContributors.\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e\u003cb\u003ePreface.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction to Rare Event Simulation\u003c\/b\u003e (\u003ci\u003eGerardo Rubino and Bruno Tuffin).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I THEORY.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Importance Sampling in Rare Event Simulation\u003c\/b\u003e (\u003ci\u003ePierre L’Ecuyer, Michel Mandjes and Bruno Tuffin).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Splitting Techniques\u003c\/b\u003e (\u003ci\u003ePierre L’Ecuyer, François Le Gland, Pascal Lezaud\u003c\/i\u003e \u003ci\u003eand Bruno Tuffin).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Robustness Properties and Confidence Interval Reliability Issues\u003c\/b\u003e (\u003ci\u003ePeter W. Glynn, Gerardo Rubino and Bruno Tuffin).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II APPLICATIONS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Rare Event Simulation for Queues\u003c\/b\u003e (\u003ci\u003eJosé Blanchet and Michel Mandjes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Markovian Models for Dependability Analysis\u003c\/b\u003e (\u003ci\u003eGerardo Rubino and Bruno Tuffin).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Rare Event Analysis by Monte Carlo Techniques in Static Models\u003c\/b\u003e (\u003ci\u003eHéctor Cancela, Mohamed El Khadiri and Gerardo Rubino).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Rare Event Simulation and Counting Problems\u003c\/b\u003e (\u003ci\u003eJosé Blanchet and Daniel Rudoy).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Rare Event Estimation for a Large-Scale Stochastic Hybrid System with Air Traffic Application\u003c\/b\u003e (\u003ci\u003eHenk A. P. Blom, G. J. (Bert) Bakker and Jaroslav Krystul).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Particle Transport Applications\u003c\/b\u003e (\u003ci\u003eThomas Booth).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Rare Event Simulation Methodologies in Systems Biology\u003c\/b\u003e (\u003ci\u003eWerner Sandmann).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eGerardo Rubino,\u003c\/b\u003e Research Director, the Institute of Computer Science and Random Systems Research (INRIA) INRIA Rennes - Bretagne Atlantique Research Centre Campus universitaire de Beaulieu. \u003c\/p\u003e \u003cp\u003e\u003cb\u003eBruno Tuffin,\u003c\/b\u003e Research Associate, the INRIA IRISA\/INRIA.  \u003c\/p\u003e\u003cp\u003eIn 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. \u003c\/p\u003e \u003cp\u003eMonte 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.  \u003c\/p\u003e\u003cp\u003eGraduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989913387237,"sku":"NP9780470772690","price":140.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470772690.jpg?v=1761785885","url":"https:\/\/k12savings.com\/products\/rare-event-simulation-using-monte-carlo-methods-isbn-9780470772690","provider":"K12savings","version":"1.0","type":"link"}