• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.135-142
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• 2001

A multivariate statistic based on interdirection is proposed for detecting dependence among many vectors. The asymptotic distribution of the proposed statistic is derived under the null hypothesis of independence. Also we find the asymptotic distribution under the alternatives contiguous to the null hypothesis, which is needed for later use of computing relative efficiencies.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.27-33
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• 2001

Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive an asymptotic distribution for stopping time.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.313-318
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• 1999

Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive an asymptotic distribution.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.13-32
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• 1994

Let A(n) and B(n) be sequences of $m \times m$ random matrices with a joint asymptotic distribution as $n \to \infty$. The asymptotic distribution of the ordered roots of $$\mid$A(n) - f B(n)$\mid$ = 0$ depends on the multiplicity of the roots of a determinatal equation involving parameter roots. This paper treats the asymptotic distribution of the roots of the above determinantal equation in the case where some of parameter roots are zero. Furthermore, we apply our results to deriving the asymptotic distributions of the eigenvalues of the MANOVA matrix in the noncentral case when the underlying distribution is not multivariate normal and some parameter roots are zero.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.449-458
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• 2004

Data envelopment analysis (DEA) estimators have been widely used in productivity analysis. The asymptotic distribution of DEA estimator derived by Kneip et al. (2003) is too complicated and abstract for analysts to use in practice, though it should be appreciated in its own right. This paper provides another way to express the limit distribution of the DEA estimator in a tractable way.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.139-144
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• 1990

For the first-order bilinear time series model $X_t = aX_{t-1} + e_i + be_{t-1}X_{t-1}$ where ${e_i}$ is a sequence of independent normal random variables with mean 0 and variance $\sigma^2$, the asymptotic distribution of sample autocarrelation function is obtained and shown to follow a normal distribution. The variance of the asymptotic distribution is of a complicated form and hence a bootstrap estimate of the variance is proposed for large sample inference. This result can be used to distinguish between different bilinear models.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.19-27
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• 1999

An orientation-shift model for unit random vectors in $R^3$ is defined. The Euler angles are introduced to parametrize orientation-shifts and their moment estimators are found. Through the analytic perturbation method, the asymptotic distributions of the estimators are obtained.

• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.47-56
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• 1997

The asymptotic distribution of the extended Yule-Walker estimates of a mixed ARMA process is derived. Also, a recursive algorithm is derived to calculate the extended Yule-Walker estimates recursively, which is a generalization of the Levinson-Durbin algorithm.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.155-170
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• 1997

We propose an integer-valued MA(q) process with Poisson disturbance. Its various properties are discussed such as the joint distribution, time reversibility and regression. We derive the asymptotic distribution of autocovariance function and estimators of the parameters in the suggested model. We also consider the relationship between INMA(q) and M/D/.infty. processes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.543-546
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• 1996

Recently, some research has been done to analyze the asymptotic behavior of queue length distribution in ATM (Asynchronous Transfer Mode) multiplexer. In this paper, we relate this asymptotic behavior with the asymptotic behavior of decreasing cell loss probability when the buffer capacity is increased. We find with reasonable assumptions that the asymptotic rate of queue length distribution is the same as that of decreasing cell loss probability. Even under different priority control schemes and traffic classes, we find that this asymptotic rate of the individual cell loss probability of each traffic class does not change. As a consequence, we propose the upper bound of cell loss probability of each traffic class when a priority control scheme is employed. This bound is computationally feasible in a real-time. The numerical examples will be provided to validate this finding.