• 제목/요약/키워드: maximal moment inequality

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MAXIMAL INEQUALITIES AND AN APPLICATION UNDER A WEAK DEPENDENCE

  • HWANG, EUNJU;SHIN, DONG WAN
    • 대한수학회지
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    • 제53권1호
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    • pp.57-72
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    • 2016
  • We establish maximal moment inequalities of partial sums under ${\psi}$-weak dependence, which has been proposed by Doukhan and Louhichi [P. Doukhan and S. Louhichi, A new weak dependence condition and application to moment inequality, Stochastic Process. Appl. 84 (1999), 313-342], to unify weak dependence such as mixing, association, Gaussian sequences and Bernoulli shifts. As an application of maximal moment inequalities, a functional central limit theorem is developed for linear processes with ${\psi}$-weakly dependent innovations.

Complete convergence for weighted sums of AANA random variables

  • 김태성;고미화
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 추계 학술발표회 논문집
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    • pp.209-213
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    • 2002
  • We study maximal second moment inequality and derive complete convergence for weighted sums of asymptotically almost negatively associated(AANA) random variables by applying this inequality. 2000 Mathematics Subject Classification : 60F05

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A FUNCTIONAL CENTRAL LIMIT THEOREM FOR LINEAR RANDOM FIELD GENERATED BY NEGATIVELY ASSOCIATED RANDOM FIELD

  • Ryu, Dae-Hee
    • 충청수학회지
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    • 제22권3호
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    • pp.507-517
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    • 2009
  • We prove a functional central limit theorem for a linear random field generated by negatively associated multi-dimensional random variables. Under finite second moment condition we extend the result in Kim, Ko and Choi[Kim,T.S, Ko,M.H and Choi, Y.K.,2008. The invariance principle for linear multi-parameter stochastic processes generated by associated fields. Statist. Probab. Lett. 78, 3298-3303] to the negatively associated case.

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ALMOST SURE MARCINKIEWICZ TYPE RESULT FOR THE ASYMPTOTICALLY NEGATIVELY DEPENDENT RANDOM FIELDS

  • Kim, Hyun-Chull
    • 호남수학학술지
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    • 제31권4호
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    • pp.505-513
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    • 2009
  • Let {$X_k;k{\in}N^d$} be centered and identically distributed random field which is asymptotically negative dependent in a certain case. In this note we prove that for $p{\alpha}$ > 1 and ${\alpha}$ > ${\frac{1}{2}}$ $E{\mid}X_1{\mid}^p(log^+{\mid}X_1{\mid}^{d-1})$ < ${\infty}$ if and only if ${\sum}_n{\mid}n{\mid}^{p{\alpha}-2}P$($max_{1{\leq}k{\leq}n{\mid}S_k{\mid}}$ > ${\epsilon}{\mid}n{\mid}$) < ${\infty}$ for all ${\epsilon}$ > 0, where log$^+$x = max{1,log x}.