• Title/Summary/Keyword: Strong Law of Large Numbers

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A convergence of fuzzy random variables

  • Hong, Dug-Hun
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.75-82
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    • 2003
  • In this paper, a general convergence theorem of fuzzy random variables is considered. Using this result, we can easily prove the recent result of Joo et al. (2001) and generalize the recent result of Kim(2000).

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A NOTE ON FELLER`S THEOREM

  • Hong, dug-Hun
    • Communications of the Korean Mathematical Society
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    • v.14 no.2
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    • pp.425-428
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    • 1999
  • In this note we have generalization of Feller`s theorem to real separable Banach spaces, from which we obtain easily Chow-Robbins “fair" games problem in the Banach spaces.aces.

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ON LIMIT BEHAVIOURS FOR FELLER'S UNFAIR-FAIR-GAME AND ITS RELATED MODEL

  • An, Jun
    • Journal of the Korean Mathematical Society
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    • v.59 no.6
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    • pp.1185-1201
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    • 2022
  • Feller introduced an unfair-fair-game in his famous book [3]. In this game, at each trial, player will win 2k yuan with probability pk = 1/2kk(k + 1), k ∈ ℕ, and zero yuan with probability p0 = 1 - Σk=1 pk. Because the expected gain is 1, player must pay one yuan as the entrance fee for each trial. Although this game seemed "fair", Feller [2] proved that when the total trial number n is large enough, player will loss n yuan with its probability approximate 1. So it's an "unfair" game. In this paper, we study in depth its convergence in probability, almost sure convergence and convergence in distribution. Furthermore, we try to take 2k = m to reduce the values of random variables and their corresponding probabilities at the same time, thus a new probability model is introduced, which is called as the related model of Feller's unfair-fair-game. We find out that this new model follows a long-tailed distribution. We obtain its weak law of large numbers, strong law of large numbers and central limit theorem. These results show that their probability limit behaviours of these two models are quite different.

A NEW KIND OF THE LAW OF THE ITERATED LOGARITHM FOR PRODUCT OF A CERTAIN PARTIAL SUMS

  • Zang, Qing-Pei
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.5
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    • pp.1041-1046
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    • 2011
  • Let {X, $X_{i};\;i{\geq}1$} be a sequence of independent and identically distributed positive random variables. Denote $S_n= \sum\array\\_{i=1}^nX_i$ and $S\array\\_n^{(k)}=S_n-X_k$ for n ${\geq}$1, $1{\leq}k{\leq}n$. Under the assumption of the finiteness of the second moments, we derive a type of the law of the iterated logarithm for $S\array\\_n^{(k)}$ and the limit point set for its certain normalization.

Convergence of weighted sums of linearly negative quadrant dependent random variables (선형 음의 사분 종속확률변수에서 가중합에 대한 수렴성 연구)

  • Lee, Seung-Woo;Baek, Jong-Il
    • Journal of Applied Reliability
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    • v.12 no.4
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    • pp.265-274
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    • 2012
  • We in this paper discuss the strong law of large numbers for weighted sums of arrays of rowwise LNQD random variables by using a new exponential inequality of LNQD r.v.'s under suitable conditions and we obtain one of corollary.

ON ALMOST SURE CONVERGENCE OF NEGATIVELY SUPERADDITIVE DEPENDENT FOR SEMI-GAUSSIAN RANDOM VARIABLES

  • BAEK, JONG-IL;SEO, HYE-YOUNG
    • Journal of applied mathematics & informatics
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    • v.39 no.1_2
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    • pp.145-153
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    • 2021
  • When {Xni|1 ≤ i ≤ n, n ≥ 1} be an array of rowwise negatively superadditive dependent(NSD) for semi-Gaussian random variables and {ani|1 ≤ i ≤ n, n ≥ 1} is an array of constants, we study the almost sure convergence of weighted sums ∑ni=1 aniXni under some appropriate conditions and we obtain some corollaries.

THE ALMOST SURE CONVERGENCE OF WEIGHTED AVERAGES UNDER NEGATIVE QUADRANT DEPENDENCE

  • Ryu, Dae-Hee
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.885-893
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    • 2009
  • In this paper we study the strong law of large numbers for weighted average of pairwise negatively quadrant dependent random variables. This result extends that of Jamison et al.(Convergence of weight averages of independent random variables Z. Wahrsch. Verw Gebiete(1965) 4 40-44) to the negative quadrant dependence.

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ON COMPLETE CONVERGENCE AND COMPLETE MOMENT CONVERGENCE FOR A CLASS OF RANDOM VARIABLES

  • Wang, Xuejun;Wu, Yi
    • Journal of the Korean Mathematical Society
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    • v.54 no.3
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    • pp.877-896
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    • 2017
  • In this paper, the complete convergence and complete moment convergence for a class of random variables satisfying the Rosenthal type inequality are investigated. The sufficient and necessary conditions for the complete convergence and complete moment convergence are provided. As applications, the Baum-Katz type result and the Marcinkiewicz-Zygmund type strong law of large numbers for a class of random variables satisfying the Rosenthal type inequality are established. The results obtained in the paper extend the corresponding ones for some dependent random variables.

CONVERGENCE RATES FOR SEQUENCES OF CONDITIONALLY INDEPENDENT AND CONDITIONALLY IDENTICALLY DISTRIBUTED RANDOM VARIABLES

  • Yuan, De-Mei
    • Journal of the Korean Mathematical Society
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    • v.53 no.6
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    • pp.1275-1292
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    • 2016
  • The Marcinkiewicz-Zygmund strong law of large numbers for conditionally independent and conditionally identically distributed random variables is an existing, but merely qualitative result. In this paper, for the more general cases where the conditional order of moment belongs to (0, ${\infty}$) instead of (0, 2), we derive results on convergence rates which are quantitative ones in the sense that they tell us how fast convergence is obtained. Furthermore, some conditional probability inequalities are of independent interest.