• East Asian mathematical journal
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• 제36권1호
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• pp.25-34
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• 2020

The classical limit theorems like strong law of large numbers, central limit theorems and law of iterated logarithms are fundamental theories in probability and statistics. These limit theorems are proved under additivity of probabilities and expectations. In this paper, we investigate strong law of large numbers under sub-linear expectation which generalize the classical ones. We give strong law of large numbers under sub-linear expectation with respect to the partial sums and some conditions similar to Petrov's. It is an extension of the classical Chung type strong law of large numbers of Jardas et al.'s result. As an application, we obtain Chung's strong law of large number and Marcinkiewicz's strong law of large number for independent and identically distributed random variables under the sub-linear expectation. Here the sub-linear expectation and its related capacity are not additive.

• 대한수학회보
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• 제38권1호
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• pp.55-63
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• 2001

In this paper, we derive a general strong law of large numbers and a general weak law of large number for normed weighted sums of pairwise negative quadrant dependent random variables with the common distribution function.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.153-161
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• 2001

In this paper, a strong law of large numbers for sums of stationary and ergodic fuzzy random variables is obtained.

• 대한수학회논문집
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• 제12권3호
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• pp.769-778
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• 1997

In this paper, we obtain a strong law of large number for sums of level-wise independent and level-wise identically distributed fuzzy random variables.

• Journal of applied mathematics & informatics
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• 제16권1_2호
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• pp.419-427
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• 2004

In this paper we establish the Hajeck-Renyi type inequality and derive the strong law of large numbers for asymptotically quadrant sub-independent random variables.

• 대한수학회지
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• 제43권6호
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• pp.1325-1338
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• 2006

For double arrays of constants ${a_{ni},\;1{\leq}i{\leq}k_n,\;n{\geq}1}$ and sequences of negatively orthant dependent random variables ${X_n,\;n{\geq}1}$, the conditions for strong law of large number of ${\sum}^{k_n}_{i=1}a_{ni}X_i$ are given. Both cases $k_n{\uparrow}{\infty}\;and\;k_n={\infty}$ are treated.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.451-457
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• 2002

We derive the strong laws of large numbers for weighted averages of partial sums of random variables which are either associated or negatively associated. Our theorems extend and generalize strong law of large numbers for weighted sums of associated and negatively associated random variables of Matula(1996; Probab. Math. Statist. 16) and some results in Birkel(1989; Statist. Probab. Lett. 7) and Matula (1992; Statist. Probab. Lett. 15 ).

• 대한수학회논문집
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• 제22권2호
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• pp.315-321
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• 2007

We show an exponential inequality for negatively associated and strictly stationary random variables replacing an uniform boundedness assumption by the existence of Laplace transforms. To obtain this result we use a truncation technique together with a block decomposition of the sums. We also identify a convergence rate for the strong law of large number.

• Journal of the Korean Statistical Society
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• 제34권1호
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• pp.1-9
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• 2005

In this paper we establish the Hajeck-Renyi type inequality for asymptotically quadrant sub-independent random variables and derive the strong law of large numbers by this inequality.

• Journal of the Korean Data and Information Science Society
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• 제14권1호
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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).