• Title/Summary/Keyword: infinitely divisible

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A NEW CRITERION FOR MOMENT INFINITELY DIVISIBLE WEIGHTED SHIFTS

  • Hong T. T. Trinh
    • Communications of the Korean Mathematical Society
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    • v.39 no.2
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    • pp.437-460
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    • 2024
  • In this paper we present the weighted shift operators having the property of moment infinite divisibility. We first review the monotone theory and conditional positive definiteness. Next, we study the infinite divisibility of sequences. A sequence of real numbers γ is said to be infinitely divisible if for any p > 0, the sequence γp = {γpn}n=0 is positive definite. For sequences α = {αn}n=0 of positive real numbers, we consider the weighted shift operators Wα. It is also known that Wα is moment infinitely divisible if and only if the sequences {γn}n=0 and {γn+1}n=0 of Wα are infinitely divisible. Here γ is the moment sequence associated with α. We use conditional positive definiteness to establish a new criterion for moment infinite divisibility of Wα, which only requires infinite divisibility of the sequence {γn}n=0. Finally, we consider some examples and properties of weighted shift operators having the property of (k, 0)-CPD; that is, the moment matrix Mγ(n, k) is CPD for any n ≥ 0.

MULTIVARIATE DISTRIBUTIONS WITH SELFDECOMPOSABLE PROJECTIONS

  • Sato, Ken-Iti
    • Journal of the Korean Mathematical Society
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    • v.35 no.3
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    • pp.783-791
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    • 1998
  • A random vector X on $R^{d}$ with the following properties is constructed: the distribution of X is infinitely divisible and not selfdecomposable, but every linear transformation of X to a lower-dimensional space has a selfdecomposable distribution.

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DIVISORS OF THE PRODUCTS OF CONSECUTIVE INTEGERS

  • Koh, Young-Mee;Ree, Sang-Wook
    • Communications of the Korean Mathematical Society
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    • v.17 no.3
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    • pp.541-550
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    • 2002
  • In this Paper, We look at 3 Simple function L assigning to an integer n the smallest positive integer n such that any product of n consecutive numbers is divisible by n. Investigated are the interesting properties of the function. The function L(n) is completely determined by L(p$\^$k/), where p$\^$k/ is a factor of n, and satisfies L(m$.$n) $\leq$ L(m)+L(n), where the equality holds for infinitely many cases.

DIRECT PRODUCTED W*-PROBABILITY SPACES AND CORRESPONDING AMALGAMATED FREE STOCHASTIC INTEGRATION

  • Cho, Il-Woo
    • Bulletin of the Korean Mathematical Society
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    • v.44 no.1
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    • pp.131-150
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    • 2007
  • In this paper, we will define direct producted $W^*-porobability$ spaces over their diagonal subalgebras and observe the amalgamated free-ness on them. Also, we will consider the amalgamated free stochastic calculus on such free probabilistic structure. Let ($A_{j},\;{\varphi}_{j}$) be a tracial $W^*-porobability$ spaces, for j = 1,..., N. Then we can define the corresponding direct producted $W^*-porobability$ space (A, E) over its N-th diagonal subalgebra $D_{N}\;{\equiv}\;\mathbb{C}^{{\bigoplus}N}$, where $A={\bigoplus}^{N}_{j=1}\;A_{j}\;and\;E={\bigoplus}^{N}_{j=1}\;{\varphi}_{j}$. In Chapter 1, we show that $D_{N}-valued$ cumulants are direct sum of scalar-valued cumulants. This says that, roughly speaking, the $D_{N}-freeness$ is characterized by the direct sum of scalar-valued freeness. As application, the $D_{N}-semicircularityrity$ and the $D_{N}-valued$ infinitely divisibility are characterized by the direct sum of semicircularity and the direct sum of infinitely divisibility, respectively. In Chapter 2, we will define the $D_{N}-valued$ stochastic integral of $D_{N}-valued$ simple adapted biprocesses with respect to a fixed $D_{N}-valued$ infinitely divisible element which is a $D_{N}-free$ stochastic process. We can see that the free stochastic Ito's formula is naturally extended to the $D_{N}-valued$ case.

ON SELF-SIMILAR STOCHASTIC INTEGRAL PROCESSES

  • Kim, Joo-Mok
    • Communications of the Korean Mathematical Society
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    • v.9 no.4
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    • pp.961-973
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    • 1994
  • A stochastics process $X = {X(t) : t \in T}$, with an index set T, is said to be infinitely divisible (ID) if its finite dimensional distributions are all ID. An ID process X is said to be a stochastic integral process if $X = {X(t) : t \in T} =^D {\int f_td\Lambda : t \in T}$ where $f : T \times S \to R$ is a deterministic function and $\Lambda$ is an ID random measure on a $\delta$-ring S of subsets of an arbitrary non-empty set S with the property; there exists an increasing sequence ${S_n}$ of sets in S with $U_n S_n = S$. Here $=^D$ denotes equality in all finite dimensional distributions.

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