• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.55-69
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• 2006

This paper presents a new class of multivariate distributions with Pareto where dependence among the components is characterized by a latent random variable. The new class includes several multivariate and bivariate models of Marshall and Olkin type. It is found the bivariate distribution with Pareto is positively quadrant dependent and its mixture. Some important structural properties of the bivariate distributions with Pareto are discussed. The distribution of minimum in a competing risk Pareto model is derived.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.45-61
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• 2002

We consider the problem of estimating binomial proportions in the presence of nonignorable nonresponse using the Bayesian selection approach. Inference is sampling based and Markov chain Monte Carlo (MCMC) methods are used to perform the computations. We apply our method to study doctor visits data from the Korean National Family Income and Expenditure Survey (NFIES). The ignorable and nonignorable models are compared to Stasny's method (1991) by measuring the variability from the Metropolis-Hastings (MH) sampler. The results show that both models work very well.

• Bulletin of the Korean Chemical Society
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• v.27 no.12
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• pp.2101-2103
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• 2006

• Journal of Labour Economics
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• v.38 no.1
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• pp.1-30
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• 2015

The aggregate matching function is estimated to explain dynamics among job seekers, vacancies and new hires in Korea. Due to measurement errors inherent in vacancies data, I introduce a latent variable for job openings and use the instrumental variables to correct its endogeneity. Matching efficiency is also estimated using some explanatory variables like job seekers' characteristics and public employment services. The result shows that Korea's matching function also exhibits a constant returns to scale.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.407-420
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• 1998

This paper is concerned with selecting covariates to be included in building linear random effects models designed to analyze clustered response normal data. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting premising subsets of covariates. The approach reformulates the linear random effects model in a hierarchical normal and point mass mixture model by introducing a set of latent variables that will be used to identify subset choices. The hierarchical model is flexible to easily accommodate sign constraints in the number of regression coefficients. Utilizing Gibbs sampler, the appropriate posterior probability of each subset of covariates is obtained. Thus, In this procedure, the most promising subset of covariates can be identified as that with highest posterior probability. The procedure is illustrated through a simulation study.

• Journal of Welding and Joining
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• v.10 no.2
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• pp.32-42
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• 1992

A method of optimization of process parameters in Arc Welding has been discussed in this paper. The method of investigation is based on the numerical calculation of weld bead by a finite element method and non-linear optimization technique is applied to estimated the optimization process parameters from the numerical calculation. The common package program(ANSYS 4.4A) was used to obtain the process parameters for a thin plate arc welding (TIG, CO$_{2}$). The results on some test are satisfactory and the used method of this paper is a useful guide to the optimum welding condition.

• Journal of Families and Better Life
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• v.2 no.1
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• pp.79-92
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• 1984

The purpose of this study is to identify family stress and to specify family stress and socio-psychological resources which are associated variable. For the evidence of this topic, research was conducted on 258 married persons dwelling in seoul. The questionnare was composed of Family Stressor Inventory referred by McCubbin's FILE(1981) and Sarason's LES(1979) and Socio-Psychological Family Resources Inventory referred by McCubbin's FIRM(1983). This study offers to us that family income significantly has positive correlation with socio-psychological family resources and family income is potential variable which intensifies family tension or burden. This study touched only some variables, moreover, this is only a starting-point of family stress study in Korea. So further studies would consider latent variables, process, limited situation, family interaction pattern, family orientation, etc., and subjective variables would be reflected.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.301-311
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• 1997

The purpose of this study is to construct a structural equation model and to analyze causal relationships among variables related to attitudes to science using structural equation modeling(SEM) with LISREL VII. The sample consisted of 483 10th grade boys from a general high school in Pusan, Korea. The questionnaires (ABC-attitude scale: affection, behavioral intention, cognition scale of attitude towards science) were developed by the researcher through a pilot study. And other instruments have modified previous ones. Five instruments were used in this study: GALT(group assessment of logical thinking), MTSlS(modified test of science inquiry skill), ABC-attitude scale, MSAS(modified scientific attitude scale), CSAT(common science achievement test). Structural equation modeling with LISREL VII($J\ddot{o}reskog$ & $S\ddot{o}rbom,$ 1993) was employed to estimate the causal inferences about hypothesized relationships among observed data sets. Three competing models consisted of five latent variable(scientific thinking ability, science inquiry skill, attitude towards science, scientific attitude, science achievement) - lP(inquiry preceding) model, AP(attitude preceding) model and AM(attitude mediating) model - were developed. Among these competing models, IP model satisfied the observed data sets. The causal relationships among "attitudes to science" and other latent variables were reliably identified. According to the results of the present study, science inquiry skill was the most significant variable that can predict science achievement. But scientific thinking ability has not directly influenced science achievement. This study suggests that inquiry based teaching-learning processes should be offered to students for improvement of science achievement. At the same time, it seems to be important to develop positive attitude towards science. Understanding of relationships among variables related to attitudes to science will be helpful to the development of science curriculum and to the design of science teaching and learning process. LISREL has been recognized as a useful approach in testing a SEM. However, in this study, LISREL approach was estimated as much more useful method for research design.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7923-7927
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• 2015

Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.399-411
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• 2008

Today, the statistical survey has been carried out variously for the decision-making and administration of the organization. We use the different items in the statistical survey according to the purpose of study. Currently, Gyeongnam province is executing the social index survey to the provincials every year. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution for this problem is data fusion technique. Data fusion is generally defined as the use of techniques that collect to combine data including multiple sources in order to raise the quality of information. But, data fusion doesn't mean the ultimate result. Therefor, efficient analysis for the fused data is also important. In this study, we suggest the application methodology of neural network by latent variable through the fused data in statistical survey.