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Student's t-Distribution and Related Stochastic Processes - SpringerBriefs in Statistics (Paperback)
  • Student's t-Distribution and Related Stochastic Processes - SpringerBriefs in Statistics (Paperback)
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Student's t-Distribution and Related Stochastic Processes - SpringerBriefs in Statistics (Paperback)

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£35.99
Paperback 99 Pages / Published: 18/09/2012
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This brief monograph is an in-depth study of the infinite divisibility and self-decomposability properties of central and noncentral Student's distributions, represented as variance and mean-variance mixtures of multivariate Gaussian distributions with the reciprocal gamma mixing distribution. These results allow us to define and analyse Student-Levy processes as Thorin subordinated Gaussian Levy processes. A broad class of one-dimensional, strictly stationary diffusions with the Student's t-marginal distribution are defined as the unique weak solution for the stochastic differential equation. Using the independently scattered random measures generated by the bi-variate centred Student-Levy process, and stochastic integration theory, a univariate, strictly stationary process with the centred Student's t- marginals and the arbitrary correlation structure are defined. As a promising direction for future work in constructing and analysing new multivariate Student-Levy type processes, the notion of Levy copulas and the related analogue of Sklar's theorem are explained.

Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN: 9783642311451
Number of pages: 99
Weight: 1825 g
Dimensions: 235 x 155 x 5 mm
Edition: 2013 ed.


MEDIA REVIEWS

"It is self-contained and summarizes the most recent results by the author related to t-distribution and their processes. ... Grigelionis has pulled together an excellent overview in Student t-distribution and processes, which has not previously been available. The book is written at a highly scholarly level and should appeal to those with an interest in applied probability methodology and applications. It should be for students who have had an advanced course in probability." (Stergios B. Fotopoulos, Technometrics, Vol. 58 (3), August, 2016)

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