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＜電子ブック＞
Tempered Stable Distributions : Stochastic Models for Multiscale Processes / by Michael Grabchak
(SpringerBriefs in Mathematics. ISSN:21918201)

版	1st ed. 2016.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2016
大きさ	XII, 118 p : online resource
著者標目	*Grabchak, Michael author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Social sciences—Mathematics FREE:Probability Theory FREE:Mathematics in Business, Economics and Finance
一般注記	Introduction -- Preliminaries -- Tempered Stable Distributions -- Limit Theorems for Tempered Stable Distributions -- Multiscale Properties of Tempered Stable Levy Processes -- Parametric Classes -- Applications -- Epilogue -- References 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 HTTP:URL=https://doi.org/10.1007/978-3-319-24927-8

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