• Bulletin of the Korean Mathematical Society
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• v.43 no.2
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• pp.277-292
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• 2006

We consider a single-server queue with service time distribution of phase type where positive customers, negative customers and disasters arrive according to a Markovian arrival process with marked transitions (MMAP). We derive simple formulae for the stationary queue length distributions. The Laplace-Stieltjes transforms (LST's) of the sojourn time distributions under the combinations of removal policies and service disciplines are also obtained by using the absorption time distribution of a Markov chain.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.433-442
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• 1999

A model for a system whose deteriorating rate depends on the state is introduced. A repairman arrives according to Poisson process and increases the state of the system by the random amount if the state is below a threshold. If the system fails at arrival of the repairman it is assumed that the system is replaced by new one. The stationary distribution function of the state of the system and the expected life length of the system are deduced.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.41-50
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• 1995

In this paper, an iterative procedure, which detects the location of the outliers and the joint estimates of the outliers effects and the model parameters in the autoregressive moving average model with two types of outliers, is proposed. The performance of the procedure is compared with the one in Chen and Liu(1993) through the Monte Carlo simulation. The proposed procedure is very robust in the sense that applies the procedures to the stationary time series model with any types of outliers.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.195-210
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• 2007

This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity ($\beta$-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.

• Structural Engineering and Mechanics
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• v.9 no.2
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• pp.141-152
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• 2000

Based on the discussion about some empirical coherency models resulted from earthquake-induced ground motion recordings at the SMART-1 array in Taiwan, and a heuristic model of the coherency function from elementary notions of stationary random process theory and a few simplifying assumptions regarding the propagation of seismic waves, a practical coherency model for spatially varying ground motions, which can be applied in aseismic analysis and design, is proposed, and the regressive coefficients are obtained using least-square fitting technique from the above recordings.

• Environmental and Resource Economics Review
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• v.9 no.3
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• pp.515-544
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• 2000

This paper shows that various fractionally integrated univariate and multivariate are remarkably successful in representing annual temperature series and also very long series of tree ring widths, which are often used as a proxy for temperature. The analysis also suggests that human recorded temperature series are not inconsistent with being generated by a stationary, long memory process. From the empirical results, we should be noted that the statistically significant positive trend coefficients may well be due to small sample sizes. These results cast some doubt on the basic assumption that global warming is definitely occurring.

• Journal of the Korean Statistical Society
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• v.12 no.2
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• pp.100-109
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• 1983

Let ${X_i}$ be a process with stationary and independent increments whose log characteristic function is expressed as $ibut-2^{-1}\sigma^2u^2t+t\int_{{0 }^c}{(exp(iux)-1-iux(i+x^2)^{-1})dv(x)}$. Our main result is taht $x^2(\int_{\y\>x}{dv(y)})/(\int_{$\mid$y$\mid$\leqx}{y^2dv(y)+\sigma^2}) \to 1$ as $x \to 0 (resp. x \to \infty)$ is necessary, and sufficient for ${X-i}$ to have ${A_t}$ and ${B_t}$ such that $(X_t-A_t)/B_t \to^D n(0,1)$ as $t \to 0 (resp. t \to \infty)$.

• Journal of the Korean Statistical Society
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• v.17 no.1
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• pp.30-45
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• 1988

Let ${X(t) : 0 \leq t < \infty}$ be a real-valued process with stationary independent increments. In this paper, we obtain necesary and sufficint condition for there to exist a positive, nondecreasing function $\beta(t)$ so that $0 < lim sup $\mid$X(t)$\mid$/\beta(t) < \infty$ a.s. both as t tends to zero and infinity. When no such $\beta(t)$ exists we give a simple integral test for whether $lim sup $\mid$X(t)$\mid$/\beta(t)$ is zero or infinity for a given $\beta(t)$.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.121-128
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• 2002

In this paper we provide a new proof of the asymptotic distributions of LAD estimators using the martingale limit theorem and show the efficiency of LAD estimators in a stationary AR(1) model setting.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.233-237
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• 2003

An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.