• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.281-292
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• 1995

In this paper the concept of strong mixing is extended to random fields, and an invariance principle is obtained for stationary strong mixing random fields.

• Structural Engineering and Mechanics
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• v.20 no.3
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• pp.293-312
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• 2005

In this paper, free vibration of rotating beam with random properties is studied. The cross-sectional area, elasticity modulus, moment of inertia, shear modulus and density are modeled as random fields and the rotational speed as a random variable. To study uncertainty, stochastic finite element method based on second order perturbation method is applied. To discretize random fields, the three methods of midpoint, interpolation and local average are applied and compared. The effects of rotational speed, setting angle, random property variances, discretization scheme, number of elements, correlation of random fields, correlation function form and correlation length on "Coefficient of Variation" (C.O.V.) of first mode eigenvalue are investigated completely. To determine the significant random properties on the variation of first mode eigenvalue the sensitivity analysis is performed. The results are studied for both Timoshenko and Bernoulli-Euler rotating beam. It is shown that the C.O.V. of first mode eigenvalue of Timoshenko and Bernoulli-Euler rotating beams are approximately identical. Also, compared to uncorrelated random fields, the correlated case has larger C.O.V. value. Another important result is, where correlation length is small, the convergence rate is lower and more number of elements are necessary for convergence of final response.

• Honam Mathematical Journal
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• v.33 no.4
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• pp.591-602
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• 2011

In this paper we establish the central limit theorem and the strong law of large numbers for linear random fields generated by identically distributed linear negative quadrant dependent random variables on $\mathbb{Z}^2$.

• Honam Mathematical Journal
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• v.34 no.2
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• pp.209-217
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• 2012

Convergence rates in the law of large numbers for i.i.d. random variables have been generalized by Gut[Gut, A., 1978. Marc inkiewicz laws and convergence rates in the law of large numbers for random variables with multidimensional indices, Ann. Probab. 6, 469-482] to random fields with all indices having the same power in the normalization. In this paper we generalize these convergence rates to the identically distributed and negatively associated random fields with different indices having different power in the normalization.

• Journal of the Chungcheong Mathematical Society
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• v.11 no.1
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• pp.35-44
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• 1998

Let {X(t), $t{\in}\mathbb{R}^n$} be a $S{\alpha}S$ H-sssis Chentsov random field with control measure m. We consider a geometric construction for L$\acute{e}$vy-Chentsov random fields and Takenaka random fields. Finally, we proved some property of conjugate classes and a.s. H$\ddot{o}$lder unboundedness of $S{\alpha}S$ H-sssis Chentsov random fields for all order ${\gamma}$ > H.

• Journal of the Chungcheong Mathematical Society
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• v.9 no.1
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• pp.115-121
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• 1996

Let $\{X(t);\;t{\in}R^n\}$ be a measurable, separable and H-sssis random fields. Here, we suppose that the increments are invariant under all Euclidean rigid body motions. We investigate some properties of H-sssis random fields and monotonicity of projection process $\{X_e(t);\;t{\in}R^1\}$ in any direction $e{\in}R^n$.

• Communications of the Korean Mathematical Society
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• v.12 no.2
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• pp.411-418
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• 1997

In this note we prove a functional central limit theorem for nonstationary linearly positive quadrant dependent random fields. We extend it to the case of random measures.

• Communications of the Korean Mathematical Society
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• v.14 no.3
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• pp.597-609
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• 1999

In this article we prove a central limit theorem for strictly stationary weakly dependent random fields with some interlaced mix-ing conditions. Mixing coefficients are not assumed. The result it basically the same to Peligrad([4]), which is CLT weakly depen-dent arrays of random variables. The proof is quite similar to the of Peligrad.

• Honam Mathematical Journal
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• v.33 no.2
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• pp.163-171
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• 2011

In this paper we provide extensions of the Marcinkiewicz Zygmund laws of large numbers for i.i.d random variables with multidimensional indices to the case of negatively dependent random fields.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.441-453
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• 2005

In this article we will introduce a real valued random field on a restricted indexed set and construct a classical asymptotic limit theorems on them. We will survey the basic properties of weakly dependent random processes and investigate two major mixing conditions for sequences of random variables. The concepts of weakly dependent sequence of random variables will be generalized to the case of random fields. Finally we will construct a central limit theorem and prove it.