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Tempered Stable Distributions: Stochastic Models for Multiscale Processes: 0 (SpringerBriefs in Mathematics) - Tapa blanda

Libro 68 de 155: SpringerBriefs in Mathematics

Grabchak, Michael

 
9783319249254: Tempered Stable Distributions: Stochastic Models for Multiscale Processes: 0 (SpringerBriefs in Mathematics)
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ISBN 10: 3319249258 ISBN 13: 9783319249254
Editorial: Springer, 2016

Sinopsis

This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. 
A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.

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Críticas

“This is a very nicely written book on tempered stable distributions. The exposition is careful and very readable. ... The book will be a very helpful source for researchers working in the area of tempered stable distributions and for all that want to apply them.” (Alexander Lindner, zbMATH 1361.60003, 2017)

Reseña del editor

This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. 
A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2016
Idioma
Inglés
ISBN 10 
3319249258
ISBN 13 
9783319249254
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
132
Contacto del fabricante
no disponible
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