• Communications for Statistical Applications and Methods
• /
• v.26 no.2
• /
• pp.91-102
• /
• 2019

In this paper, we propose a new estimation method based on a weighted linear regression framework to obtain some estimators for unknown parameters in a two-parameter Rayleigh distribution under a progressive Type-II censoring scheme. We also provide unbiased estimators of the location parameter and scale parameter which have a nuisance parameter, and an estimator based on a pivotal quantity which does not depend on the other parameter. The proposed weighted least square estimator (WLSE) of the location parameter is not dependent on the scale parameter. In addition, the WLSE of the scale parameter is not dependent on the location parameter. The results are compared with the maximum likelihood method and pivot-based estimation method. The assessments and comparisons are done using Monte Carlo simulations and real data analysis. The simulation results show that the estimators ${\hat{\mu}}_u({\hat{\theta}}_p)$ and ${\hat{\theta}}_p({\hat{\mu}}_u)$ are superior to the other estimators in terms of the mean squared error (MSE) and bias.

• Communications for Statistical Applications and Methods
• /
• v.26 no.2
• /
• pp.191-203
• /
• 2019

The problem of examining how well an assumed distribution fits the data of a sample is of significant and must be examined prior to any inferential process. The observed failure time data of items are often not wholly available in reliability and life-testing studies. Lowering the expense and period associated with tests is important in statistical tests with censored data. Goodness-of-fit tests for perfect data can no longer be used when the observed failure time data are progressive Type II censored (PC) data. Therefore, we propose goodness-of-fit test statistics and a graphical method based on generalized Lorenz curve for PC data from a location-scale distribution. The power of the proposed tests is then assessed through Monte Carlo simulations. Finally, we analyzed two real data set for illustrative purposes.

• IE interfaces
• /
• v.24 no.4
• /
• pp.341-350
• /
• 2011

This paper considers a problem of locating both distribution centers and retailers in a zone-dependent two-level distribution network where either a distribution center or a retailer should be located in each zone. Customer demands of each zone should be satisfied directly from either its own distribution center or its own retailer being supplied from a distribution center of another zone. The objective of the proposed problem is to minimize total cost being composed of distribution center/retailer setup costs and transportation costs. In the analysis, the problem is proved to be NP-hard, so that a branch-and-bound algorithm is derived for the problem. Numerical experiments show that the proposed branch-and-bound algorithm provides the optimal solution efficiently for some small problems.

• IE interfaces
• /
• v.17 no.4
• /
• pp.450-458
• /
• 2004

S-Distribution Center supplies parts to three plants of K-automobile manufacturing company. Since the three plants employ the JIT production system, it is important for S-Distribution Center to deliver small quantities of parts frequently and quickly on time. This paper presents a case study on the improvement of order-picking operation in S-Distribution Center. The study is focused on the reductions of move time and waiting time by redesigning the parts storage location, picking-order terminal location, retrieval policy, and equipment operation policy. The proposed operation system for S-Distribution Center is evaluated through a simple computation analysis and computer simulation. Furthermore, the reducible numbers of equipment and order pickers are investigated by performing a sensitivity analysis.

• Proceedings of the KIEE Conference
• /
• 2000.07a
• /
• pp.510-512
• /
• 2000

This paper describes the voltage induced at neutral line and the proper location of lightning arrester in combined 22.9 kV class distribution line jointed overhead line and cable each other Modeling is established in ATP Draw to perform simulation. Simulated distribution line at this paper consists of distribution line 4.2km and underground distribution line 2km. Overvoltage and induced voltage are analyzed at several point of combined line. Analysis results was compared to select the best point to install arrester. Such analysis technology will be applied to obtaining capacity and location of arrester in the similar combined distribution line.

• Communications for Statistical Applications and Methods
• /
• v.6 no.1
• /
• pp.275-283
• /
• 1999

In order to estimate a parameter $(\alpha,\beta^r), r\epsilonN$, in a distribution belonging to a location-scale family we usually use best invariant estimator (BIE) and best unbiased estimator (BUE). But in some conditions Ryu (1996) showed that BIE is better than BUE. In this paper we calculate risks of BIE and BUE in a normal and an exponential distribution respectively and calculate a percentage risk improvement exponential distribution respectively and calculate a percentage risk improvement (PRI). We find the sample size n which make no significant differences between BIE and BUE in a normal distribution. And we show that BIE is always significantly better than BUE in an exponential distribution. Also simulation in a normal distribution is given to convince us of our result.

• Journal of the Korea Safety Management & Science
• /
• v.13 no.1
• /
• pp.195-202
• /
• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• Journal of Korea Water Resources Association
• /
• v.46 no.11
• /
• pp.1103-1113
• /
• 2013

In this study, determination methods of the pressure monitoring location in water distribution system were introduced and applied to sample pipe network. The best determination method of the pressure monitoring location was suggested and applied to the real city pipe network. Three kinds of determination methods of pressure monitoring locations are categorized such as the sensitivity analysis according to changing roughness coefficient, pressure contribution analysis, and sensitivity analysis according to changing demand. Further-more, pressure contribution analysis and sensitivity analysis from the results of unsteady analysis were conducted and compared each other. From the results, the most accurate and simplest method was selected in this study. Therefore, the best method can be applied for the pressure management or leakage detection as a determination method of pressure monitoring location in water distribution system.

• Communications for Statistical Applications and Methods
• /
• v.3 no.3
• /
• pp.291-297
• /
• 1996

In this paper, we propose the jackknife estimator and the bootstrap estimator of Gini index of the two-parameter exponential distribution when the location parameter $\theta$ is unknown and the scale parameter $\sigma$is known. Sinilarly, we propose the bias location parameter $\theta$ and the scale parameter $\sigma$ are unknown. The bootstrap estimator is more efficient than the other estimators when the location parameter $\theta$is unknown and the scale parameter $\sigma$ is known, and the bias corrected estimator is more efficient than the MLE when both the location parameter $\theta$ and the scale parameter $\sigma$are unknown.

• Journal of Korean Society of Water and Wastewater
• /
• v.22 no.1
• /
• pp.149-157
• /
• 2008

The reduction of leakage is a major issue of the South Korea water industry. The inclusion of pressure dependent leakage terms in network analysis allows the application of optimization techniques to identify the most effective means of reducing water leakage in distribution networks. This paper proposes a method to find optimal setting and location of control valve for reducing leakage efficiently. The proposed search method differs from previous methods for addressing optimal valve location problem and improves the GA simulation time with guaranteeing for getting the global optimal solution. The strength of this method has been demonstrated by means of case studies. This allows the procedure of optimization to be more robust and computational efficient.