• Journal of the Korean Statistical Society
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• 제32권1호
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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.

• 호남수학학술지
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• 제27권3호
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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.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제11권2호
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• pp.139-147
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• 2004

Let {<$\mathds{X}_t$} be an m-dimensional linear process of the form $\mathbb{X}_t\;=\sumA,\mathbb{Z}_{t-j}$ where {$\mathbb{Z}_t$} is a sequence of stationary m-dimensional negatively associated random vectors with $\mathbb{EZ}_t$ = $\mathbb{O}$ and $\mathbb{E}\parallel\mathbb{Z}_t\parallel^2$ < $\infty$. In this paper we prove the central limit theorems for multivariate linear processes generated by negatively associated random vectors.

• 대한수학회논문집
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• 제17권1호
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• pp.95-102
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• 2002

A central limit theorem is obtained for a stationary multivariate linear process of the form (equation omitted), where { $Z_{t}$} is a sequence of strictly stationary m-dimensional associated random vectors with E $Z_{t}$ = O and E∥ $Z_{t}$∥$^2$ < $\infty$ and { $A_{u}$} is a sequence of coefficient matrices with (equation omitted) and (equation omitted).ted)..ted).).

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.615-623
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• 2001

A functional central limit theorem is obtained for a stationary multivariate linear process of the form (no abstract. see full-text) where{ $Z_{t}$} is a sequence of strictly stationary m-dimensional negatively associated random vectors with E $Z_{t}$=O and E∥ $Z_{t}$∥$^2$<$\infty$ and { $A_{u}$} is a sequence of coefficient matrices with (no abstract. see full-text) and (no abstract. see full-text).text).).

• Communications for Statistical Applications and Methods
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• 제17권5호
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• pp.639-645
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• 2010

We consider a subdiagonal bilinear model and give sufficient conditions for the associated Markov chain defined by Pham (1985) to be uniformly ergodic and then obtain the $\beta$-mixing property for the given process. To derive the desired properties, we employ the results of generalized random coefficient autoregressive models generated by a matrix-valued polynomial function and vector-valued polynomial function.

• Journal of the Korean Statistical Society
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• 제25권2호
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• pp.243-253
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• 1996

Let X and Y be random vectors in R$^{n}$ . A random vector X is 'more associated' than Y if and only if P(X $\in$ A ∩ B) - P(X $\in$ A)P(X $\in$ B) $\geq$ P(Y $\in$ A ∩ B)-P(Y $\in$ A)P(Y $\in$ B) for all open upper sets A and B. By requiring the above inequality to hold for some open upper sets A and B various notions of positive dependence orderings which are weaker than 'more associated' ordering are obtained. First a general theory is given and then the results are specialized to some concepts of a particular interest. Various properties and interrelationships are derived.

• 한국경영과학회지
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• 제4권1호
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• pp.59-64
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• 1979

The application of optimization techniques to the planning of industrial, economic, administrative and military activities with random technological coefficients has been extensively studied in the literature. Stochastic (linear) programs with simple recourse essentially model the allocation of scarce resources under uncertainty with linear penalties associated with shortages or surplus. This work on a problem with a discrete random resource vector, "The allocation of aircraft under uncertain demand" given in (1), is easily and efficiently handled by the application of the recently developed Wets' algorithm (8) for solving stochastic programs with simple recourse, which approves that such class of stochastic problems can be solved with the same efficiency as solving linear programs of the same size. It is known that the algorithm is also applicable to stochastic programs with continuous random demands for their approximate solutions.

• 응용통계연구
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• 제7권1호
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• pp.103-112
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• 1994

본 논문에서는 비정상(단위근) 시계열이 포함된 다변량 시계열 자료에서 단위근에 해당되는 계수행렬 추정량의 극한 분포가 정상시계열의 유무에 상관없이 일정하다는 것을 밝혔다. 또한 단위근만 존재하는 다변량 시계열에서 다중단위근을 검정하는 검정통계량을 제안하였다.

• Journal of the Korean Statistical Society
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• 제23권2호
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• pp.223-238
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• 1994

A random vector $\b{X} = (X_1,\cdots,X_n)$ is weakly associated if and only if for every pair of partitions $\b{X}_1 = (X_{\pi(1)},\cdots,X_{\pi(k)}), \b{X}_2 = (X_{\pi(k+1),\cdots,X_{\pi(n)})$ of $\b{X}, P(\b{X}_1 \in A, \b{X}_2 \in B) \geq P(\b{X}_1 \in A)\b{P}(\b{X}_2 \in B)$ whenever A and B are open upper sets and $\pi$ is a permutation of ${1,\cdots,n}$. In this paper, we develop notions of weak positive dependence, which are weaker than a positive version of negative association (weak association) but stronger than positive orthant dependence by arguments similar to those of Shaked. We also illustrate some concepts of a particular interest. Various properties and interrelationships are derived.