Stochastic Disorder Problems

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Éditeur :

Springer


Collection :

Probability Theory and Stochastic Modelling

Paru le : 2019-03-12

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Description

This monograph focuses on those stochastic quickest detection tasks in disorder problems that arise in the dynamical analysis of statistical data. These include quickest detection of randomly appearing targets, of spontaneously arising effects, and of arbitrage (in financial mathematics). There is also currently great interest in quickest detection methods for randomly occurring intrusions in information systems and in the design of defense methods against cyber-attacks. The author shows that the majority of quickest detection problems can be reformulated as optimal stopping problems where the stopping time is the moment the occurrence of disorder is signaled. Thus, considerable attention is devoted to the general theory of optimal stopping rules, and to its concrete problem-solving methods.
The exposition covers both the discrete time case, which is in principle relatively simple and allows step-by-step considerations, and the continuous-time case, which often requires more technical machinery such as martingales, supermartingales, and stochastic integrals. There is a focus on the well-developed apparatus of Brownian motion, which enables the exact solution of many problems. The last chapter presents applications to financial markets.

Researchers and graduate students interested in probability, decision theory and statistical sequential analysis will find this book useful.

Pages
397 pages
Collection
Probability Theory and Stochastic Modelling
Parution
2019-03-12
Marque
Springer
EAN papier
9783030015251
EAN PDF
9783030015268

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
4987 Ko
Prix
126,59 €
EAN EPUB
9783030015268

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
27269 Ko
Prix
126,59 €