• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.279-288
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• 1999

In many cases where the conventional binomial distribution fails to apply to real world data, it is mainly due to the lack of independence among Bernoulli trials. Several authors have proposed models that are useful when independence assumption is not satisfied. In this paper, one proposed model is adapted, and estimators of dependence related parameter that is crucial in defining that model are considered. Simulation is performed to compare two estimators(method of moment estimator and maximum likelihood estimator) of dependence related parameter, and conclusions are made.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.99-105
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• 1979

In Thoman and Bain and Schafer and Sheffield, procedures for testing the equality of the scale parameters of two Weibull populations with a common shape parameter and procedures for selecting the Weibull population with the largest scale parameter are given. We give, in this paper, a modified procedure for the above testing and selection problems, which is more powerful than those previoulsy given.

• Water for future
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• v.29 no.1
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• pp.129-139
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• 1996

It is very important to select appropriate distributions for hydrological data in planning and designing hydraulic structures. Also, it is necessary to check whether the selected distribution reproduces the statistical characteristics of the real data. In this study, the parameters of the two- and three-parameter gamma, two- and three-parameter lognormal, Gumbel, two- and three-parameter log-Gumbel, GEV, log-Pearsonn type III, two- and three-parameter Weibull, four- and five-parameter Wakeby distributions were estimated for the rainfall data of 22 sites in Korea with 7 different durations based on the methods of moments, probability weighted moments, and maximum likelihood. And the validity conditions were checked for the estimated parameters. The separation effect for each distribution was examined throught 10,000 simulations using the estimated parameters. As results, the separation effect was the smallest: log-Pearson type III for moment method, log-Pearson type III and GEV for probability weighted moment method, and GEV for maximum likelihood method. However, it is large for the two-parameter distributions.

• Korean Journal of Metals and Materials
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• v.49 no.4
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• pp.275-280
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• 2011

This paper focuses on reliability prediction of long-term creep strength for Modified 9Cr-1Mo steel (Gr. 91) which is considered as one of the structural materials of next generation reactor systems. A "Z-parameter" method was introduced to describe the magnitude of standard deviation of creep rupture data to the master curve which can be plotted by log stress vs. The larson-Miller parameter (LMP). Statistical analysis showed that the scattering of the Z-parameter for the Gr. 91 steel well followed normal distribution. Using this normal distribution of the Z-parameter, the various reliability curves for creep strength design, such as stress-time temperature parameter reliability curves (${\sigma}$-TTP-R curves), stress-rupture time-reliability curves (${\sigma}-t_{r}-R$ curves), and allowable stress-temperature- reliability curves ([${\sigma}$]-T-R curves) were reasonably drawn, and their results are discussed.

• Bulletin of the Korean Mathematical Society
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• v.39 no.1
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• pp.23-31
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• 2002

A scale parameter is the principal parameter to be estimated, since it corresponds to one of the main reliability characteristics, namely the average time to failure. To provide robustness of scale estimators to gross errors in the data, we apply the Huber minimax approach in time to failure models of the statistical reliability theory. The minimax valiance estimator of scale is obtained in the important particular case of the exponential distribution.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1209-1217
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• 2006

For the mixture of shifted Poisson distributions, a method of parameter estimation is proposed. The range of the shifted parameters are estimated first and for each shifted parameter set EM algorithm is applied to estimate the other parameters of the distribution. Among the estimated parameter sets, one with minimum likelihood for given data is to be set as the final estimate. In simulation experiments, the suggested estimation method shows to have a good performance.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.489-499
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• 2000

We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.47-58
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• 1990

Abstract A regionalized daily streamflow model using a modified retention parameter in the SCS method was developed to predict the daily streamflow of a natural series for Korean watersheds. Model verification showed that it is possible to use the model for extending short period records in a gaged watershed or for predicting daily streamflow in any ungaged watershed, with reasonable accuracy by simply inputing the name of the watershed boundary, the watershed size, the latitude and longitude of the watershed, and the daily areal rainfall.

• Bulletin of the Korean Mathematical Society
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• v.48 no.4
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• pp.839-845
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• 2011

In this paper, we consider the cusum of squares test for the dispersion parameter in stochastic differential equation models. It is shown that the test has a limiting distribution of the sup of a Brownian bridge, unaffected by the drift parameter estimation. A simulation result is provided for illustration.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.330-332
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• 1992

This paper tries to evaluate the control performance of systeme in cases of parameter perturbations. Six cases of the root distribution and location changes of each characteristic roots by the parameter perturbation are considered as evaluation factors. A qualitative evaluation is performed through several simulations. These results will be used as a basic data for the complete analysis of the control performance.