• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.129-148
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• 2007

Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.76-82
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• 2005

In this paper, validation of Driver Steering Model has been conducted. The comparison between the simulation model and vehicle test results shows that the model is very feasible for describing combined human driver and actual vehicle dynamic behaviors. The 3D vehicle model is consisted of 6-DOF sprung mass and 4-quarter car model for vehicle body dynamics. Powertrain model including differential gear and Pacejka tire model are applied. The driver steering model is also validated with vehicle test result. The driver steering model is based on angle and displacement error from the desired path, recognized by driver.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.221-234
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• 2014

Purpose: The Purpose of this study is to develop a model for predicting agent churn group in the cosmetics industry. We develope two models, pattern model and matrix model, which are compared regarding the prediction accuracy of churn agents. Finally, we try to conclude if there is statistically significant difference between two models by empirical study. Methods: We develop two models using the part of RFM(Recency, Frequency, Monetary) method which is one of customer segmentation method in traditional CRM study. In order to ensure which model can predict churn agents more precisely between two models, we used CRM data of cosmetics company A in China. Results: Pattern model and matrix model have been developed. we find out that there is statistically significant differences between two models regarding the prediction accuracy. Conclusion: Pattern model and matrix model predict churn agents. Although pattern model employed the trend of monetary mount for six months, matrix model that used the amount of sales per month and the duration of the employment is better than pattern model in prediction accuracy.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.69-74
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• 2013

According to the axial torsion applied at power transmission and the vibration from the roughness of road surface, this paper analyzes the stresses on two kinds of universal joint model. As stress and deformation at model 2 becomes smaller than model 1 on structural analysis, model 2 is more stabilized than model 1. The natural frequencies at model 1 and 2 are 7,040 and 9,540 Hz respectively. As the natural frequency range of model 2 becomes higher than model 1, model 2 becomes safer than model 1. Critical frequencies at these models are calculated through harmonic response analyses. On critical frequencies at model 1 and 2, the stress at model 2 becomes lower than 2 times as much as model 1 and the deformation at model 2 becomes lower than 4 times as much as model 1. Model 2 on durability is thought to become better than model 1. This study result is applied with the design of safe universal joint and it can be useful to improve the durability by predicting prevention against the deformation due to its vibration.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• The Journal of Fisheries Business Administration
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• v.44 no.1
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• pp.59-70
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• 2013

The purpose of this paper is to integrate various models of price formation and let the data choose the most proper model. After the data choose the proper model, one can analyze the price formation process and demand structures for fishery resources under the restriction of Korean fisheries regulations. This study suggests the integrated model including quasi-linear price formation model, Translog price formation model, AIDS price formation model and Lewbel price formation model as level variables. It also suggests another integrated model including AIDS price formation model, Rotterdam price formation model, Latinen-Theil price formation model and Neves price formation model as difference variables. The empirical results show that the AIDS price formation model is the most preferred in both level and difference variables of fishery resources. The estimated parameters show that all sample species have (-) sign of price flexibilities, thus following the law of demand. The scale flexibilities of all species are estimated as (-) sign, thus being adapted to the theory. The contribution and results are summarized as follows. First, the integrated model of fishery market demand has been developed and the data can choose the proper model without arbitrary choice of the researcher. Second, the fishery market demand structure could be analyzed in a way different from the ordinary demand analysis, which is based upon price flexibility and scale flexibility. Third, the integrated model for fishery resources can be used easily when catching restrictions are imposed by policies.

• The Pure and Applied Mathematics
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• v.20 no.1
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• pp.59-70
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• 2013

The purpose of this study was to develop a zero-inflated Rasch (ZI-Rasch) model, a combination of the Rasch model and the ZIP model. The ZI-Rasch model was considered in this study as an appropriate alternative to the Rasch model for zero-inflated data. To investigate the relative appropriateness of the ZI-Rasch model, several analyses were conducted using PROC NLMIXED procedures in SAS under various simulation conditions. Sets of criteria for model evaluations (-2LL, AIC, AICC, and BIC) and parameter estimations (RMSE, and $r$) from the ZI-Rasch model were compared with those from the Rasch model. In the data-model fit indices, regardless of the simulation conditions, the ZI-Rasch model produced better fit statistics than did the Rasch model, even when the response data were generated from the Rasch model. In terms of item parameter ${\lambda}$ estimations, the ZI-Rasch model produced estimates similar to those of the Rasch model.

• Korean Management Science Review
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• v.28 no.1
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• pp.11-24
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• 2011

In this paper, we develop a new conceptual framework for finding new business opportunities in the cloud computing environment. We propose a service model framework for cloud computing business. In the service concept of the proposed business model, we categorize customer needs and service offering value, while we analyze customer behavior for developing revenue model. In addition, we analyze cloud computing market drivers for finding an evolution path of the proposed business model. Finally, we develop cloud computing business strategies for Korean IT service industry.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.190-193
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• 2009

A recently reported simple phenomenological constitutive model (SK) demonstrated comparable or better data description capability to/than one of the rigorous and physics-based models, the PTW model. The simple SK model is believed to be an efficient model for practical applications where an extensive computation is needed, and can serve as a rigorous comparison standard for the development of a physics-based model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.177-186
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• 2003

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correlated response variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.