• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.31-37
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• 1996

A hierarchical loglinear model comparison method is developed which is based on the well kmown partitioned likelihood ratio statistiss. For any paels, we can regard the difference of the geedness of fit statistics as the variation explained by a full model, and develop a partial test to compare a full model with a reduced model in that hierarchy. Note that this has similar arguments as that of the regression analysis.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.761-770
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• 2012

We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.131-145
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• 2003

A strategic plan for an immediate situation must be present in a business enterprise to deal actively and efficiently with the demand environment of new customer. The purpose of this paper is to provide research about the manufacturing strategy situations of the Korean manufacturing company. And this paper is a part of Modeling on Manufacturing Strategy. We emphasizes the importance of dynamism and complexity on the competitive environment, and classify the manufacturing strategy by trade-off model, cumulative model, sandcone model, strategic fit model, and competitiveness model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.599-606
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• 2010

This paper presents dynamic analysis of FCEV (Fuel Cell Electric Vehicle) Turbo Blower. To analyze the dynamic characteristics of Turbo Blower, finite element model which consists of solid elements is constructed. Evaluation of stress for safety of rotor sleeve due to centrifugal force, Shrink fit analysis in maximum rotation speed is performed. Rotor dynamic analysis of Turbo blower is conducted using Campbell diagram and FEA (Finite element analysis) results are compared with experimental results to evaluate of validity of finite element model. To evaluate of Structure vibration characteristics, Modal analysis and forced vibration analysis are performed through FEA and experiment.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.75-85
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• 1994

In this paper, I introduce the goodness-of-fit test statistics for exponential distribution using accelerated life test data. The ALT lifetime data were obtained by assuming step-stress ALT model, specially TRV model introduced by DeGroot and Goel(1979). The critical values are obtained for proposed test statistics, Kolmogorov-Smirnov, Kuiper, Watson, Cramer-von Mises, Anderson-Darling type, under various sample sizes and significance levels. The powers of the five test statistic are compared through Monte-Cairo simulation technique.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.339-351
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• 1998

Designs for discriminating between two linear regression models are studied under $\Lambda$-type optimalities maximizing the measure for the lack of fit for the designs with fixed model inadequacy. The problem of selecting an appropriate $\Lambda$-type optimalities is shown to be closely related to the estimation method. $\Lambda$-type optimalities for the least squares and minimum bias estimation methods are considered. The minimum bias designs are suggested for the designs invariant with respect to the two estimation methods. First order minimum bias designs optimal under $\Lambda$-type optimalities are then derived. Finally for the case where the lack of fit test is significant, an approach to the construction of a second order design accommodating the optimal first order minimum bias design is illustrated.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.275-287
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• 1998

The goal of this paper is to suggest the goodness-of-fit test statistic for the no effect model. The comparisons of powers on test statistics are conducted with three types alternative modles.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.235-240
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• 2000

In this paper a test of fit for exponentiality and we propose the estimator of Kullback-Leibler Information functions using the data from accelerated life tests. This acceleration model is assumed to be a tampered random variable model. The procedure is applicable when the exponential parameter based on the data from accelerated life tests is or is not specified under null hypothesis. Using Simulations, the power of the proposed test based on use condition of accelerated life test under alternatives is compared with that of other standard tests in the small sample.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.602-607
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• 2007

The heavy duty diesel engine must have a large output for maintaining excellent mobility. The compacted graphite iron (CGI) is a material currently under study for the engine demanded for high torque, durability, stiffness and fatigue. In this study, three dimensional finite element model of a heavy-duty diesel engine was developed to conduct the stress analysis by using property of CGI. The FE model of the heavy duty diesel engine section consisting with four half cylinder was selected. The heavy duty diesel engine section include cylinder block, cylinder head, liner, bearing cap, bearing and bolt. The loading conditions of engine are pre-fit load, assembly force and gas force.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.263-271
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• 2013

This study presents a fuzzy varying coefficient regression model after deleting the outliers to improve the feasibility and effectiveness of the fuzzy regression model. The objective of our methodology is to allow the fuzzy regression coefficients to vary with a covariate, and simultaneously avoid the impact of data contaminated by outliers. In this paper, fuzzy regression coefficients are represented by Gaussian fuzzy numbers. We also formulate suitable goodness of fit to evaluate the performance of the proposed methodology. An example is given to demonstrate the effectiveness of our methodology.