• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.47-59
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• 2020

In this paper, we present the longitudinal Markov binary regression model with t-link function when its transition order is known or unknown. It is assumed that logit or probit models are considered in binary regression models. Here, t-link function can be used for more flexibility instead of the probit model since the t distribution approaches to normal distribution as the degree of freedom goes to infinity. A Markov regression model is considered because of the longitudinal data of each individual data set. We propose Bayesian method to determine the transition order of Markov regression model. In particular, we use the deviance information criterion (DIC) (Spiegelhalter et al., 2002) of possible models in order to determine the transition order of the Markov binary regression model if the transition order is known; however, we compute and compare their posterior probabilities if unknown. In order to overcome the complicated Bayesian computation, our proposed model is reconstructed by the ideas of Albert and Chib (1993), Kuo and Mallick (1998), and Erkanli et al. (2001). Our proposed method is applied to the simulated data and real data examined by Sommer et al. (1984). Markov chain Monte Carlo methods to determine the optimal model are used assuming that the transition order of the Markov regression model are known or unknown. Gelman and Rubin's method (1992) is also employed to check the convergence of the Metropolis Hastings algorithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.3
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• pp.240-244
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• 2010

The surface segregation and surface order near the order-disorder phase transition of FeCo alloy was studied through Monte Carlo simulation of an Ising type model Hamiltonian. The results showed that the proper choice of Hamiltonian parameters could reproduce the recent observation of surface order above the transition temperature and that the field term played dominant role.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.135-145
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• 2014

The present study surveys Bayesian modeling structure for inferences about transition probabilities of Markov chain. The motivation of the study came from the data that shows transitional behaviors of emotionally disturbed children undergoing residential treatment program. Dirichlet distribution was used as prior for the multinomial distribution. The analysis with real data was implemented in WinBUGS programming environment. The performance of the model was compared to that of alternative approaches.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.161-164
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• 2006

The sales of consumer durables are composed of first time purchases and replacement purchases. Since the sales for most mature durable products are dominated by replacement sales, it is necessary to develop a model incorporating replacement component of sales in order to forecast total sales accurately. Several single product diffusion models incorporating replacement demand have been developed, but research addressing the multi-product diffusion models has not considered replacement sales. In this paper, we propose a model based on consumer choice behavior that simultaneously captures the diffusion and the replacement process for multi-product relationships. The proposed model enables the division of replacement sales into repurchase by previous users and transition purchase by users of different products. As a result, the model allows the partitioning of the total sales according to the customer groups (first-time buyers, repurchase buyers, and transition buyers), which allows companies to develop their production and marketing plans based on their customer mix. We apply the proposed model to the Korean automobile market, and compare the fitting and forecasting performance with other Bass-type multi-product models.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.53-61
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• 1985

The purpose of the study is to establish models of land use prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-disciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-use projection strategy emerged as a synthesis of the probability transition model and the discriminant-annlysis model. A discriminant model is applied to all pixels in CheJoo landscape plane to predict the most likely change in land use. The probability transition model provides the number of these pixels that will convert to different land use in a gives future time increment. The synthetic model predicts the future change in land use and its volume of pixels in the landscape plane.

• Bulletin of the Korean Chemical Society
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• v.14 no.2
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• pp.255-258
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• 1993

Molecular dynamics (MD) calculations were carried out in order to investigate the effect of MD cell size to predict the melting phenomena of A-type zeolite. We studied two model systems: a pseudocell of $(T_2O_4Na)_n$, (L= 12.264 $^{\AA}$, N= 84) and a true-cell of (SiAlO$_4Na)_n$. (L= 24.528 $^{\AA}$, N= 672), where T is Si or Al. The radial and bond angle distribution functions of T(Si, Al)-O-T(Si, Al) and diffusion coefficients of T and O were reported at various temperatures. For the true-cell model, the melting temperature is below 1500 K and probably around 1000 K, which is about 600-700 K lower than the pseudocell model. Although it took more time (about 30 times longer) to obtain the molecular trajectories of the true-cell model than those of the pseudocell model, the true-cell model gave more realistic structural transition for the A-type zeolite, which agrees with experiment.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.99-100
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• 2014

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.1-7
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• 2015

When the steam is used as working fluid in fluid machinery, different from other gases as air, phase transition (steam condensation) can occur and it affects not only the flow fields, but also machine performance & efficiency. Therefore, considering phase transition phenomena in CFD calculation is required to achieve accurate prediction of steam flow and non-equilibrium wet-steam model is needed to simulate realistic steam condensing flow. In this research, non-equilibrium wet-steam model is implemented on in-house code(T-Flow), the flow fields including phase transition phenomena in convergent-divergent nozzle are studied and compared to results of advance researches.

• 한국연소학회:학술대회논문집
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• 2004.06a
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• pp.102-111
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• 2004

Partial quenching structure of turbulent diffusion flames in a turbulent mixing layer is investigated by the method of flame hole dynamics to develope a prediction model for the turbulent lift off. The present study is specifically aimed to remedy the problem of the stiff transition of the conditioned partial burning probability across the crossover condition by adopting level-set method which describes propagating or retreating flame front with specified propagation speed. In light of the level-set simulations with two model problems for the propagation speed, the stabilizing conditions for a turbulent lifted flame are suggested. The flame hole dynamics combined with level-set method yields a temporally evolving turbulent extinction process and its partial quenching characteristics is compared with the results of the previous model employing the flame-hole random walk mapping. The probability to encounter reacting' state, conditioned with scalar dissipation rate, demonstrated that the conditional probability has a rather gradual transition across the crossover scalar dissipation rate in contrast to the stiff transition of resulted from the flame-hole random walk mapping and could be attributed to the finite response of the flame edge propagation.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3429-3434
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• 2015

Background: This study analyzed predictors of regular mammography performance in Korea. In addition, we determined factors affecting regular mammography performance in life-transition aged women by applying an attitude, social influence, and self-efficacy (ASE) model. Materials and Methods: Data were collected from women aged over 40 years residing in province J in Korea. The 178 enrolled subjects provided informed voluntary consent prior to completing a structural questionnaire. Results: The overall regular mammography performance rate of the subjects was 41.6%. Older age, city residency, high income and part-time job were associated with a high regular mammography performance. Among women who had undergone more breast self-examinations (BSE) or more doctors' physical examinations (PE), there were higher regular mammography performance rates. All three ASE model factors were significantly associated with regular mammography performance. Women with a high level of positive ASE values had a significantly high regular mammography performance rate. Within the ASE model, self-efficacy and social influence were particularly important. Logistic regression analysis explained 34.7% of regular mammography performance and PE experience (${\beta}=4.645$, p=.003), part-time job (${\beta}=4.010$, p=.050), self-efficacy (${\beta}=1.820$, p=.026) and social influence (${\beta}=1.509$, p=.038) were significant factors. Conclusions: Promotional strategies that could improve self-efficacy, reinforce social influence and reduce geographical, time and financial barriers are needed to increase the regular mammography performance rate in life-transition aged.