• Communications of the Korean Mathematical Society
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• v.16 no.1
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• pp.125-135
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• 2001

In this article we investigate the dependence between components of the random vector which is given as an asymptotic limit of an array of random vectors with interlaced mixing conditions. We discuss the cross covariance of the limiting vector process and give a stronger condition to have a central limit theorem for an array of random vectors with mixing conditions.

• Communications of the Korean Mathematical Society
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• v.10 no.3
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• pp.707-714
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• 1995

In this note, we extend the concepts of linearly positive quadrant dependence to the random vectors and prove a functional central limit theorem for positively quadrant dependent sequence of $R^d$-valued or separable Hilbert space valued random elements which satisfy a covariance summability condition. This result is an extension of a functional central limit theorem for weakly associated random vectors of Burton et al. to positive quadrant dependence case.

• Journal of the Korean Statistical Society
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• v.32 no.1
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• pp.11-20
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• 2003

Let｛Ｘt｝be an m-dimensional linear process of the form (equation omitted), where｛Zt｝is a sequence of stationary m-dimensional weakly associated random vectors with EZt = O and E∥Zt∥$^2$＜$\infty$. We Prove central limit theorems for multivariate linear processes generated by weakly associated random vectors. Our results also imply a functional central limit theorem.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.3
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• pp.423-426
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• 2015

Current verification methods for on-chip memory have been implemented using coverpoints that are generated based on a single operation. These coverpoints cannot consider the influence of other memory banks in a busy state. In this paper, we propose a method in which the coverpoints account for all operations executed on different memory banks. In addition, a new constrained random vector generation method is proposed to reduce the required random vectors for the multi-operation-based coverpoints. The simulation results on NAND flash memory show 100% coverage with 496,541 constrained random vectors indicating a reduction of 96.4% compared with conventional random vectors.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.339-345
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• 1993

It is well known that distribution of functions of eigen values and vectors of a certain matrix plays an important role in multivariate analysis. This paper deals with the transformation of a correlation-type random matrix to its eigen values and vectors. Properties of the transformation are also considered. The results obtained are applied to express the joint distribution of eigen values and vectors of the correlation matrix when sample is taken from a m-variate spherical distribution.

• Journal of the Korean Mathematical Society
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• v.39 no.1
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• pp.119-126
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• 2002

For a stationary multivariate linear process of the form X$_{t}$ = (equation omitted), where {Z$_{t}$ : t = 0$\pm$1$\pm$2ㆍㆍㆍ} is a sequence of stationary linearly positive quadrant dependent m-dimensional random vectors with E(Z$_{t}$) = O and E∥Z$_{t}$∥ $^2$< $\infty$, we prove a central limit theorem.theorem.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.237-247
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• 2001

In this paper, we will introduce multivariate versions of bivariate conditionally positive dependence and the partial ordering is developed among conditionally positive lower orthant dependent(CPLOD) random vectors. This permits us to measure the degree of CPLOD-ness and to compare pairs of CPLOD random vectors. Some proper ties and closure under certain statistical operations are derived.

• Journal of the Korean Mathematical Society
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• v.56 no.2
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• pp.457-473
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• 2019

In this paper, we investigate weak laws of large numbers for weighted coordinatewise pairwise negative quadrant dependence random vectors in Hilbert spaces in the case that the decay order of tail probability is r for some 0 < r < 2. Moreover, we extend results concerning Pareto-Zipf distributions and St. Petersburg game.

• Journal of the Chungcheong Mathematical Society
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• v.32 no.3
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• pp.327-336
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• 2019

In this paper, the weak laws of large numbers for sums of asymptotically almost negatively associated random vectors in Hilbert spaces are investigated. Some results in Hien and Thanh ([3]) are generalized to asymptotically almost negatively random vectors in Hilbert space.

• Honam Mathematical Journal
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• v.27 no.3
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• pp.505-513
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• 2005

The aim of this paper is to establish a functional central limit theorem for multivariate moving average process generated by negatively associated random vectors under the finite second moments.