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Non-Markovian Stochastic Processes and their Applications: From Anomalous Diffusion To Time Series Analysis - Couverture souple

Mura, Antonio

 
9783844392296: Non-Markovian Stochastic Processes and their Applications: From Anomalous Diffusion To Time Series Analysis
Couverture souple
ISBN 10 : 3844392297 ISBN 13 : 9783844392296
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

This book represents a forward step in the comprehension of the relationships between certain non-Markovian processes and many integral-partial differential equations usually used to model systems manifesting long memory properties. The author made the book the more self consistent as possible by presenting all the advanced mathematical tools needed to understand the original parts. In particular, fractional Brownian motion and fractional Gaussian noise are presented as elementary examples of non-Markovian processes. These processes, together with FARIMA processes, can be used to model and estimate Long-Range Dependence (or long memory) in many contexts: physics, meteorology, hydrology, but also finance, economy, etc. Within the book LRD is studied, statistics and parametric methods of estimation are presented and many real data examples are provided. Then, the theory of fractional integrals and derivatives, which results very appropriate to model long-memory systems, is introduced. Finally, generalizations of the normal diffusion are investigated and, in order to find a connection with LRD, grey Brownian motion and more general non-Markovian processes are defined and studied.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book represents a forward step in the comprehension of the relationships between certain non-Markovian processes and many integral-partial differential equations usually used to model systems manifesting long memory properties. The author made the book the more self consistent as possible by presenting all the advanced mathematical tools needed to understand the original parts. In particular, fractional Brownian motion and fractional Gaussian noise are presented as elementary examples of non-Markovian processes. These processes, together with FARIMA processes, can be used to model and estimate Long-Range Dependence (or long memory) in many contexts: physics, meteorology, hydrology, but also finance, economy, etc. Within the book LRD is studied, statistics and parametric methods of estimation are presented and many real data examples are provided. Then, the theory of fractional integrals and derivatives, which results very appropriate to model long-memory systems, is introduced. Finally, generalizations of the normal diffusion are investigated and, in order to find a connection with LRD, grey Brownian motion and more general non-Markovian processes are defined and studied.

Biographie de l'auteur

Graduated cum laude at Bologna University with a thesis on topological aspects of quantum field theory, after a master in mathematical finance, he won a full scholarship in mathematical physics and got his Ph.D. in 2008. He is author of many publications in the filed of stochastic analysis, theoretical, mathematical and statistical physics.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844392297
ISBN 13 
9783844392296
Reliure
Broché
Nombre de pages
296
Coordonnées du fabricant
non disponible
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