• 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.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.311-324
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• 1999

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for an outlier problem and also analyze it in linear regression model using a Bayesian approach. Then we use the mean-shift model and SSVS(George and McCulloch, 1993)'s idea which is based on the data augmentation method. The advantage of proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability. The MCMC method(Gibbs sampler) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data and a real data.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.805-814
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• 2001

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for outliers problem and also analyze it in linear regression model using a Bayesian approach with the variance-inflation model. We will use Geweke's(1996) ideas which is based on the data augmentation method for detecting outliers in linear regression model. The advantage of the proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability The sampling based approach can be used to allow the complicated Bayesian computation. Finally, our proposed methodology is applied to a simulated and a real data.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.203-221
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• 2011

The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.189-197
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• 2019

The purpose of this study was to investigate about the effects of parental rearing behavior on self-esteem and gender role stereotype during adolescence and to reveal the mediating effect of self-esteem on adolescents' gender role strerotype. Also investigated the relationship among these variables and condition variables. For this purpose, used the Second Grade longitudianl Panel data of Middle School from the Korea Youth Panel Survay(KYPS). And the latent growth model was analyzed 3,449 men and women adolescents' cases of the first, the fourth and the sixth wave of the Korea Youth Panel Survey(KYPS) administered by Korea Institute for Youth development. And the structural equation model was used to investigate whether self-esteem mediates parental rearing behavior and male and female gender role Strerotype. The results of this study, the direct effect between variable factors showed that the more positive the parenting behavior of the second grader of middle school is, the more positive the self-esteem of male adolescents and the initial value of stereotypes of male gender role. It also affects the self-esteem of female adolescents and stereotypes of female gender roles but not statistically significant. The male gender role stereotypes were decreased in influence by the rate of change of parental rearing behaviors, and the initial value and the rate of change of self-esteem were statistically influenced to the male gender role stereotypes and the higher the self-esteem, the higher the self-esteem. However, there was no significant effect on stereotypes of female gender roles. As a result of analyzing the mediating effect of self-esteem, partially mediated between the initial value of parental rearing behavior and initial stereotype of male gender role, but there was no longitudinal mediation effect. There was no mediating effect of self-esteem between parental rearing behaviors and stereotypes of female gender roles and there was no longitudinal mediation effect. The effect of condition variable gender was found that female adolescents are more affected by paretal rearing behavior than male adolescents and also affected by the growth process. The monthly income of households influenced the initial value of parental rearing behaviors and showed a difference in parental rearing behavior according to household income. And the higher the mother 's educational level, the more the self-esteem of male adolescents was affected.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.27-40
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• 2022

In this paper, the focus on the removal noise in the binary image based on the variational Bayesian method with the Ising model. The observation and the latent variable are the degraded image and the original image, respectively. The posterior distribution is built using the Markov random field and the Ising model. Estimating the posterior distribution is the same as reconstructing a degraded image. MCMC and variational Bayesian inference are two methods for estimating the posterior distribution. However, for the sake of computing efficiency, we adapt the variational technique. When the image is restored, the iterative method is used to solve the recursive problem. Since there are three model parameters in this paper, restoration is implemented using the VECM algorithm to find appropriate parameters in the current state. Finally, the restoration results are shown which have maximum peak signal-to-noise ratio (PSNR) and evidence lower bound (ELBO).

• The korean journal of orthodontics
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• v.49 no.3
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• pp.170-180
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• 2019

Objective: The purpose of this study was to investigate the relationship between the facial skeletal patterns and the shape of the mandibular symphysis in adults with malocclusion by using a structural equation model (SEM). Methods: Ninety adults who had malocclusion and had records of facial skeletal measurements performed using cone-beam computed tomography were selected for this study. The skeletal measurements were classified into three groups (vertical, anteroposterior, and transverse). Cross-sectional images of the mandibular symphysis were analyzed using generalized Procrustes and principal component (PC) analyses. A SEM was constructed after the factors were extracted via factor analysis. Results: Two factors were extracted from the transverse, vertical, and anteroposterior skeletal measurements. Latent variables were extracted for each factor. PC1, PC2, and PC3 were selected to analyze the variations of the mandibular symphyseal shape. The SEM was constructed using the skeletal variables, PCs, and latent variables. The SEM showed that the vertical latent variable exerted the most influence on the mandibular symphyseal shape. Conclusions: The relationship between the skeletal pattern and the mandibular symphysis was analyzed using a SEM, which showed that the vertical facial skeletal pattern had the highest effect on the shape of the mandibular symphysis.

• Journal of the Korean Home Economics Association
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• v.37 no.10
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• pp.107-122
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• 1999

Based on the theoretical framework of the Double ABCX model of family stress and adaptation, this study was to analysis the causal relationships of stressors (psychological sexual, and physical wife abuse), personal resources (self-efficacy and self-esteem) and social support(emotional and informational support), appraisal(positive appraisal and downward comparisons) with adaptation (psychological well-being and somatic symptoms). Self-administered questionnaire method was used to collect data from 264 wives residing in Chonbuk-do and Kyonggi-do area. The causal model was tested and modified by the maximum likelihood method using UISREL 7 program. Results showed that wife abuse had effect on adaptation indirectly through the latent variables of personal resource and appraisal, which influenced the adaptation directly. In addition, social support indirectly affect the adaptation through personal resource and appraisal. It was also found that all these variables explained 27.6% of the total variance of wives'adaptation, and that personal resources was the most powerful variable in predicting the adaptation of the wives.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.69-72
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• 2002

본 논문에서 화자공간모델 evolution에 기반한 continuous density hidden Markov model (CDHMM)의 online 적응에 대한 새로운 기법을 제안한다. 학습화자의 a priori knowledge을 나타내는 화자공간모델은 factor analysis (FA) 또는 probabilistic principal component analysis (PPCA)와 같은 은닉변수모델(latent variable model)에 의해 효과적으로 나타내어진다. 은닉 변수모델은 화자공간모델뿐아니라 CDHMM 파라메터의 ajoint prior분포를 표시함으로, maximum a posteriori(MAP)적응기법에 직접 적용되어진다. 화자공간모델의 hyperparameters와 CDHMM파라메터를 동시에 순차적으로 적응하기 위해 quasi-Bayes (QB)추정 기술에 기반한 online 적응기법을 제안한다. 연속숫자음 인식과 관련된 화자적응 실험을 통해 제안된 기법은 적은 적응데이터에서 좋은 성능을 나타내며, 데이터가 증가함에 따라 성능이 지속적으로 증가함을 보여준다.