• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.181-193
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• 1992

This paper shows the model of a consecutive-k-out-of-n :G system with common-cause outages. The objective is to analytically derive the mean operating time between failures for a non-repairable component system. The average failure time of a system and the system availability are also considered. Then, the model is extended to a system with repairable components and unrestricted repair, in which service times are exponentially distributed.

• Communications of the Korean Mathematical Society
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• v.15 no.4
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• pp.641-648
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• 2000

The purpose of this paper is to give a necessary and sufficient condition for a smooth manifold to admit a Lorentzian metric. As an application of this result, on Lorentzian manifolds we have shown that the existence of a 1-dimensional distribution is equivalent to the existence of a non-vanishing vector field.

• Journal of Distribution Research
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• v.4 no.1
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• pp.31-49
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• 1999

The present paper discusses the current status of outsourcing of service encounter in department stores. We attempt to find if there is any significant relationship between outsourcing motive and business performance. The 30 department stores under analysis show that they vary in the degree to which they appreciate the necessity of outsourcing and also the which they employ outsourcing. It is also found that firm size influences the portion of outsourcing. The two main motives of outsourcing seem to be (i) cost saving and (ⅱ) better customer satisfaction. We find that the latter plays a more important role. However, there seems to be no significant connection between outsourcing and performance and between motives of outsourcing and performance.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.291-297
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• 2001

For a stochastic regression model in which the errors are assumed to form a stationary linear process, we show that the difference between the empirical distribution functions of the errors and the estimates of those errors converges uniformly in probability to zero at the rate of $o_{p}$ ( $n^{-}$$\frac{1}{2}$) as the sample size n increases.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.257-265
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• 1996

We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.899-911
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• 2000

In this paper, we reviewed thirteen methods for finding confidence intervals for he mean of poisson distribution. Bootstrap confidence intervals are also introduced. Two bootstrap confidence intervals are compared with the other existing eleven confidence intervals by using Monte Carlo simulation with respect to the average coverage probability of Woodroofe and Jhun (1989).

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.19-34
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• 1989

In this paper, we propose the Bayes estimators of the reliability for a system consisting of the left-truncated exponential components under the truncated normal distribution as a conjugate prior distribution and squared - error loss function on the series, parallel and k-out-of-m : G system. And we compare the proposed Bayes estimators of the system reliability each other in terms of MSE performances and stabilities by the Monte Carlo simulation.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.353-365
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• 2004

In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

• Journal of the Korean Statistical Society
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• v.7 no.2
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• pp.95-98
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• 1978

This note deals with the estimations of the variance of a normal distribution $N(\theta,c\theta^2)$ where c, the square of coefficient of variation is assumed to be known. This amounts to the estimation of $\theta^2$. The minimum variance estimator among all unbiased estimators linear in $\bar{x}^2$ and $s^2$ where $\bar{x}$ and $s^2$ are the sample mean and variance, respectively, and the minimum risk estimator in the class of all estimators linear in $\bar{x}^2$ and $s^2$ are obtained. It is shown that the suggested estimators are BAN.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.471-477
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• 2007

In this paper, we provide a new proof to correct the asymptotic normality for the estimate $\hat{C}_{pmk}\;of\;C_{pmk}$, which is one of the well-known definitions of the process capability index. Also we comment briefly on the correction of the limiting distribution for $\hat{C}_{pmk}$ and on the use of re-sampling methods for the inference of $C_{pmk}$. Finally we discuss the concept of asymptotic unbiasedness.