2001
DOI: 10.1515/dema-2001-0203
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Remarks on the Selfdecomposability and New Examples

Abstract: Abstract. The analytic property of the seljdecomposability of characteristic functions is presented from stochastic processes point of view. This provides new examples or proofs, as well as a link between the stochastic analysis and the theory of characteristic functions. A new interpretation of the famous Levy's stochastic area formula is given. Introduction and notationsThe class of selfdecomposable probability distributions, denoted as SD, (known also as the class L or Levy class L distributions), appears i… Show more

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Cited by 18 publications
(32 citation statements)
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“…It is worth noting that one can obtain expressions for cumulants without assuming analyticity. In fact, taking derivatives with respect to ζ in (27) and letting ζ → 0, one recovers the formula (28). This approach can be used to investigate cumulants and moments when they exists only up to some finite order, as in the case of Student's distribution.…”
Section: Integrated Processmentioning
confidence: 99%
“…It is worth noting that one can obtain expressions for cumulants without assuming analyticity. In fact, taking derivatives with respect to ζ in (27) and letting ζ → 0, one recovers the formula (28). This approach can be used to investigate cumulants and moments when they exists only up to some finite order, as in the case of Student's distribution.…”
Section: Integrated Processmentioning
confidence: 99%
“…Following Barndorff-Nielsen (2001), we can use X(t) in (7) to define a generalized stochastic process (random linear functional) X by s) is Λ-integrable}. By (Barndorff-Nielsen 2001, Theorem 5.1) (note that the assumptions there are not necessary by (Jurek 2001, Corollary 1), for f ∈ F Λ it holds that…”
Section: Proofs Related To Convergence Of Finite Dimensional Distribumentioning
confidence: 99%
“…(8) we see that the positive Linnik distribution is generated by itself. [12] p. [15] The distributions with LT (10) are relatively well-known because h d ¼ Zð1Þ; where h is the positive Linnik distribution with LT (10) and Z(t) is a positive strictly r-stable Lévy process independent of 1 that is an exponentially distributed r.v.…”
Section: Examples Of Sn Distributionsmentioning
confidence: 99%
“…[12] p. 244). (8) one notes it is generated by a positive Linnik distribution with parameters r 1 , b.…”
Section: Examples Of Sn Distributionsmentioning
confidence: 99%
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