• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.504-512
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• 1994

A simple proof for the random central limit theorem is given for a family of stationary linear lattice processes, which belogn to a class of 2 dimensional random fields, applying the Beveridge and Nelson decomposition in time series context. The result is an extension of Fakhre-Zakeri and Fershidi (1993) dealing with the linear process in time series to the case of the linear lattice process with 2 dimensional indices.

• Journal of applied mathematics & informatics
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• v.1 no.1
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• pp.31-42
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• 1994

In this paper we investigate an functional central limit theorem for a nonstatioary d-parameter array of associated random variables applying the crite-rion of the tightness condition in Bickel and Wichura[1971]. Our results imply an extension to the nonstatioary case of invariance principle of Burton and Kim(1988) and analogous results for the d-dimensional associated random measure. These re-sults are also applied to show a new functional central limit theorem for Poisson cluster random variables.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.117-123
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• 2005

A functional central limit theorem is obtained for a stationary linear process of the form $X_{t}= \sum\limits_{j=0}^\infty{a_{j}x_{t-j}}$, where {x_t} is a strictly stationary sequence of negatively associated random variables with suitable conditions and {a_j} is a sequence of real numbers with $\sum\limits_{j=0}^\infty|a_{j}|<\infty$.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.3
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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.

• Journal of applied mathematics & informatics
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• v.3 no.1
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• pp.89-100
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• 1996

In this paper we investigate a limit theorem for a non-statioary d-parameter array of associated random variables applying the criterion of the tightness condition in Donsker, M[1951]. Our re-sults imply an extension to the nonstatioary case of Convergence of Probability Measure of billingsley. P[1986]. and analogous results for the d-dimensional associated random measure. These results are also applied to show a new limit theorem for Poisson cluster random mea-sures.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.347-349
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• 1995

In this paper a central limit theorem on $L^P(R)$ for $1{\leq}p<{\infty}$ is obtained with an example when ${X_n}$ is a sequence of independent, identically distributed random variables on $L^P(R)$.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.851-857
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• 2011

By using Malliavin calculus, we study a central limit theorem of the cross variation related to fractional Brownian sheet with Hurst parameter H = ($H_1$, $H_2$) such that 1/4 < $H_1$ < 1/2 and 1/4 < $H_2$ < 1/2.

• The Mathematical Education
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• v.40 no.2
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• pp.345-350
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• 2001

This study suggested a teaching method to improve intuitive understanding of the statistical basic concepts about the central limit theorem with experiment. It is very hard to understand about the concept of the central limit theorem in the school mathematics class. The result of this study experiment for the class of statistics education shows that the students and mathematics teachers were interesting at this experiment. They corrected their misunderstanding about the central limit theorem by discussion for the result of experiment with team members. I think that this study can help teachers to teach the students using the experiment method.

• Communications of the Korean Mathematical Society
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• v.11 no.1
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• pp.265-272
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• 1996

In this note we prove a functional central limit theorem for linearly positive quadrant dependent(LPQD) random fields, satisfying some assumption on covariances and the moment condition $\sup_{n \in \Zeta^d} E$\mid$S_n$\mid$^{2+\rho} < \infty$ for some $\rho > 0$. We also apply this notion to random measures.

• Communications of the Korean Mathematical Society
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• v.20 no.3
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• pp.531-538
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• 2005

In this paper we derive the central limit theorem for ${\sum}_{i=1}^n\;a_{ni}\xi_i$, where ${a_{ni},\;1\;{\leq}\;i\;{\leq}\;n}$ is a triangular array of nonnegative numbers such that $sup_n{\sum}_{i=1}^n\;a_{ni}^2\;<\;{\infty},\;max_{1{\leq}i{\leq}n}a_{ni}{\rightarrow}0\;as\;n\;{\rightarrow}\;{\infty}\;and\;\xi'_i\;s$ are a linearly negative quadrant dependent sequence. We also apply this result to consider a central limit theorem for a partial sum of a generalized linear process $X_n\;=\;\sum_{j=-\infty}^\infty\;a_k+_j{\xi}_j$.