國立虎尾科技大學 |

Tempered Stable Distributions = Stochastic Models for Multiscale Processes /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Tempered Stable Distributions/ by Michael Grabchak.
Reminder of title:	Stochastic Models for Multiscale Processes /
Author:	Grabchak, Michael.
Description:	XII, 118 p.online resource. :
Contained By:	Springer Nature eBook
Subject:	Probabilities. -
Online resource:	https://doi.org/10.1007/978-3-319-24927-8
ISBN:	9783319249278

Tempered Stable Distributions = Stochastic Models for Multiscale Processes /
Grabchak, Michael.

Tempered Stable DistributionsStochastic Models for Multiscale Processes /[electronic resource] :by Michael Grabchak. - 1st ed. 2016. - XII, 118 p.online resource. - SpringerBriefs in Mathematics,2191-8198. - SpringerBriefs in Mathematics,.

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.

ISBN: 9783319249278

Standard No.: 10.1007/978-3-319-24927-8doiSubjects--Topical Terms:

527847
Probabilities.

LC Class. No.: QA273.A1-274.9

Dewey Class. No.: 519.2

Tempered Stable Distributions = Stochastic Models for Multiscale Processes /
LDR:02617nam a22004215i 4500 001 980592
003 DE-He213
005 20200704165036.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319249278 $9 978-3-319-24927-8
024 7 $a 10.1007/978-3-319-24927-8 $2 doi
035 $a 978-3-319-24927-8
050 4 $a QA273.A1-274.9
050 4 $a QA274-274.9
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a PBWL $2 thema
082 0 4 $a 519.2 $2 23
100 1 $a Grabchak, Michael. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1070659
245 1 0 $a Tempered Stable Distributions $h [electronic resource] : $b Stochastic Models for Multiscale Processes / $c by Michael Grabchak.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XII, 118 p. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Mathematics, $x 2191-8198
505 0 $a Introduction -- Preliminaries -- Tempered Stable Distributions -- Limit Theorems for Tempered Stable Distributions -- Multiscale Properties of Tempered Stable Levy Processes -- Parametric Classes -- Applications -- Epilogue -- References.
520 $a 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.
650 0 $a Probabilities. $3 527847
650 0 $a Economics, Mathematical . $3 1253712
650 1 4 $a Probability Theory and Stochastic Processes. $3 593945
650 2 4 $a Quantitative Finance. $3 669372
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319249254
776 0 8 $i Printed edition: $z 9783319249261
830 0 $a SpringerBriefs in Mathematics, $x 2191-8198 $3 1255329
856 4 0 $u https://doi.org/10.1007/978-3-319-24927-8
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)