• Water for future
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• v.8 no.1
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• pp.80-88
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• 1975

In this paper the authors established the best fit distribution function by applying the concept of probabiaity to the annual minimum flow of nine areas along the Nakdong river basin which is one of the largest Korean rivers and calculated the probable minimum flow suitable to those distribution function. Lastly, the authors tried to establish the best method to estimate the probable minimun flow by comparing some frequency analysis methods. The results obtained are as follows (1) It was considered that the extremal distribution type III was the most suitable one in the distributional types as a result of the comparision with Exponential distribution, Log-Normal distribution, Extremal distribution type-III and so on. (2) It was found that the formula of extremal distribution type-II for the estimation of probable minimum flow gave the best result in deciding the probable minimum flow of the Nakdong river basin. Therfore, it is recommended that the probable minimum flow should be estimated by using the extremal distribution type-III method. (3) It could be understood that in the probable minimum flow the average non-excessive probability appeared to be $Po{\fallingdotseq}1-\frac{1}{2T}$ and gave the same values of the probable variable without any difference in the various methods of plotting technique.

• Magazine of the Korean Society of Agricultural Engineers
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• v.21 no.4
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• pp.108-117
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• 1979

In order to obtain the basic data for design of water structures which can be contributed to the planning of water use. Best fitted distribution function and the equations for the probable minimum flow were derived to the annual minimum flow of five subwatersheds along Geum River basin. The result were analyzed and summarized as follows. 1. Type III extremal distribution was considered as a best fit one among some other distributions such as exponential and two parameter lognormal distribution by $x^2$-goodness of fit test. 2. The minimum flow are analyzed by Type III extremal distribution which contains a shape parameter $\lambda$, a location parameter ${\beta}$ and a minimum drought $\gamma$. If a minimum drought $\gamma=0$, equations for the probable minimum flow, $D_T$, were derived as $D_T={\beta}e^{\lambda}1^{y'}$, with two parameters and as $D_T=\gamma+(\^{\beta}-\gamma)e^{{\lambda}y'}$ with three parameters in case of a minimum drought ${\gamma}>0$ respectively. 3. Probable minimum flow following the return periods for each stations were also obtained by above mentioned equations. Frequency curves for each station are drawn in the text. 4. Mathematical equation with three parameters is more suitable one than that of two parameters if much difference exist between the maximum and the minimum value among observed data.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.229-241
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• 1997

We consider discrimination curve and minimum dwell time for Poisson distribution and Poisson-power function distribution. Let the random variable X has Poisson distribution with mean .lambda.. For the hypothesis testing H$\_$0/:.lambda. = t vs. H$\_$1/:.lambda. = d (d$\_$0/ if X.leq.c. Since a critical value c can not be determined to satisfy both types of errors .alpha. and .beta., we considered discrimination curve that gives the maximum d such that it can be discriminated from t for a given .alpha. and .beta.. We also considered an algorithm to compute the minimum dwell time which is needed to discriminate at the given .alpha. and .beta. for the Poisson counts and proved its convergence property. For the Poisson-power function distribution, we reject H$\_$0/ if X.leq..'{c}.. Since a critical value .'{c}. can not be determined to satisfy both .alpha. and .beta., similar to the Poisson case we considered discrimination curve and computation algorithm to find the minimum dwell time for the Poisson-power function distribution. We prosent this algorithm and an example of computation. It is found that the minimum dwell time algorithm fails for the Poisson-power function distribution if the aiming error variance .sigma.$\^$2/$\_$2/ is too large relative to the variance .sigma.$\^$2/$\_$1/ of the Gaussian distribution of intensity. In other words, if .ell. is too small, we can not find the minimum dwell time for a given .alpha. and .beta..

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.521-529
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• 2015

Statistical process control techniques have been greatly implemented in industries for improving product quality and saving production costs. As a primary tool among these techniques, control charts are widely used to detect the occurrence of assignable causes. In most works on the control charts it considered the problem of monitoring the mean and variance, and the quality characteristic of interest is normally distributed. In some situations monitoring of the minimum and maximum values is more important and the quality characteristic of interest is the Weibull distribution rather than a normal distribution. In this paper, we consider the statistical design of minimum and maximum control charts when the distribution of the quality characteristic of interest is Weibull. The proposed minimum and maximum control charts are applied to the wind data. The results of the application show that the proposed method is more effective than traditional methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.33-39
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• 2015

Power supplying capacity of the distribution feeder should be maintained within thermal capacity of the wire. This paper presents the minimum spanning tree based load balancing technique to release multiple overloading of distribution feeders. In order to minimize number of involved backup feeders, Dijkstra and Prim algorithm are adopted to construct minimum spanning tree. Simulation testing result based on part of KEPCO's commercial distribution systems shows effectiveness of proposed scheme.

• Journal of the Korean Institute of Navigation
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• v.18 no.4
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• pp.155-169
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• 1994

The minimum temperatures are important element in the daily human life, the climatic classification, and so on. In this study, the authors aim to make an analysis the distribution characteristics of minimum temperatures of 95 weather stations in Korea by using the Climatological Standard Normals of Korea VolumeI, VolumeII, and the Climatological Standard Normals of North Korea. The important results are as follows 1) The daily, fifthly, and tenthly minimum temperatures show the highest rate of occurrance on 14th of January( Occurrance rate : 56.6% ), 16~20th of January( 37.6% ), and the middle ten days of January( 82.1% ) respectively. 2) In the regional distribution of minimum temperatures in winter, the values of northern part, inland area, and west coastal region are lower than those of southern, coastal, and east coastal regions respectively. And, bigger cities and industrial area( Seoul, Incheon, Daejeon, Daegu, etc. ) have larger values than the its vicinities. 3) When the daily minimum temperature is $0^{\circ}C$ and less, the days of northern part, inland area, and wests coastal region are higher than those of southern, coastal, and east coastal regions respectively.

• International Journal of Contents
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• v.3 no.1
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• pp.1-8
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• 2007

The distributions of the minimum correlated F-variable arises in many applied statistical problems including simultaneous analysis of variance (SANOVA), equality of variance, selection and ranking populations, and reliability analysis. In this paper, negative binomial sampling technique is employed to derive the distributions of the minimum of chi-square variables and hence the distributions of the minimum correlated F-variables. The work presented in this paper is divided in two parts. The first part is devoted to develop some combinatorial identities arised from the negative binomial sampling. These identities are constructed and justified to serve important purpose, when we deal with these distributions or their characteristics. Other important results including cumulants and moments of these distributions are also given in somewhat simple forms. Second, the distributions of minimum, chisquare variable and hence the distribution of the minimum correlated F-variables are then derived within the negative binomial sampling framework. Although, multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of the distributions. The computation methods we adopted are exact and no interpolations are involved.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.805-809
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• 2006

In this paper a shrinkage estimator for the measure of dispersion of the inverse Gaussian distribution with known mean is proposed. Also we compare the relative bias and relative efficiency of the proposed estimator with respect to minimum variance unbiased estimator.

• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.3
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• pp.138-144
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• 1987

This study was conducted to pursue the normalization of frequency distribution by making approach the coefficient of skewness to nearly zero tbrough SMEMAX transformation and to get probable minimum flows can be acquired by means of transforrnation equation which has been derivated by SMEMAX method to the annual minimum flow series of five watersheds along Geum river basin. The results obtained through SMEMAX method were compared with probable minimum flows according to return periods by Type III extremal distribution which has been determined as the best fitted one among probablility distributions for the analysis of minimum flow. All the results obtained through this study are summarized as follows. 1.SMEMAX transformation based on median value was proved to be the best method when the coefficient of skewness has less reliability because of the short duration for the observation and were not affected by accidental outliers. 2.SMEMAX transformation has found to be the best one for the coefficient of skewness to be made nearly zero in comparison with log and cubic root transformation. 3.Probable minimum flows according to the return periods were derivated by transformation equations obtained through theoretical analysis of SMEM AX transformation. 4.In general, probable minimum flows by SMEMAX method were appeared as higher values in the range of five and twenty years and as lower ones in the range of below than five and more than fifty years in return periods respectively, in comparison with the results of type III extremal distribution. 5.Relative errors in the probable minimum flows of SMEMAX method to the results of type III extremal distribution were shown to be within ten percent except those of one hundred years in return periods. 6.SMEMAX method was also confirmed to be useful for the analysis of minimum flow frequency as well as flood frequency analysis.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.311-319
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• 2013

Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.