• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.148-154
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• 2009

In recent days, large-sized flat-panel display (FPD) has been increasingly applied to computer monitors and TVs. Mura defects, appearing as low contrast or non-uniform brightness region, sometimes occur in manufacturing of the Thin-Film Transistor Liquid-Crystal Displays (TFT-LCD). Implementation of automatic Mura inspection methods is necessary for TFT-LCD production. Various existing Mura detection methods based on regression diagnostics, surface fitting and data transformation have been presented with good performance. This paper proposes an efficient Mura detection method that is based on a regression diagnostics using studentized residuals for automatic Mura inspection of FPD. The input image is estimated by a linear model and then the studentized residuals are calculated for filtering Mura regions. After image dilation, the proposed threshold is determined for detecting the non-uniform brightness region in TFT-LCD by means of monitoring the every pixel in the image. The experimental results obtained from several test images are used to illustrate the effectiveness and efficiency of the proposed method for Mura detection.

• Journal of Distribution Science
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• v.13 no.12
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• pp.33-40
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• 2015

Purpose - Given an increase in the consumption of plums, prices have fluctuated in an unstable manner, making it difficult for farmhouses to sell the product. This study intends to provide information on the cultivation and sale of plums to consumers, thus enabling producers to utilize relevant information to analyze the types of plums that are preferred and consumed by users. Research design, data, and methodology - In this study, a survey was conducted on plum consumption by a consumer panel established and operated by the Rural Development Administration in December 2009. The objective was to identify the purchasing awareness of plums and to analyze panel data from 2010 to 2013 using a linear regression model, a Tobit model, and a panel regression model to derive the purchase characteristics. Results - The outcome of the survey on plums is as follows. Plums are purchased because they are good for the health (90.6%), which means that most customers purchase plums for their health benefits. When plums are in season, the purchase rate is 94.8%, indicating that most plums are purchased when they are in season and that selling plums when they are out of season is difficult. Therefore, we sell most plums in the correct season, and the rest of the plums need to be processed and then sent to markets. The strongest reason for not purchasing plums is that they are difficult to process for consumption (63.1%), followed by the reason that the fruit is unfamiliar (15.5%). Regarding solutions for increasing the consumption of plums, the answers were as follows: distribute a recipe for plums (36.9%), advertise its effect through TV or the press (31.1%), and develop various processed products (15.6%). When customers decide to pick out plums, the major considerations were freshness (4.43), safe to eat (4.16), price (3.96), size (3.87), brand (3.28), and discount event (2.62). Freshness is important for decision making and safe to eat was more important than price because plums are washed and processed into plum jam. According to the results of the linear regression model, a higher family income results in a higher purchasing amount. However, the amount of plums purchased by a person was reduced if his or her income increased. Compared with individuals who used other purchasing agents on weekdays, those who used the traditional market turned out to purchase a higher amount of plums on the weekdays. Conclusions - Considering that numerous people purchase plums for their health benefits, promoting the consumption of plums is anticipated as being successful if they can be produced safely for consumption and for inclusion in recipes and various processed foods, and to promote eco-friendly agricultural practices.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.957-981
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• 2017

A generalized linear mixed model is an extension of a generalized linear model that allows random effect as well as provides flexibility in developing a suitable model when observations are correlated or when there are other underlying phenomena that contribute to resulting variability. We describe maximum likelihood estimation methods for logistic regression models that include random effects - the Laplace approximation, Gauss-Hermite quadrature, adaptive Gauss-Hermite quadrature, and pseudo-likelihood. Applications are provided with social science problems by analyzing the effect of mental health and life satisfaction on volunteer activities from Korean welfare panel data; in addition, we observe that the inclusion of random effects in the model leads to improved analyses with more reasonable inferences.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.26-29
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• 2000

drawbead expert models are developed for calculating drawbead restraining force and drawbead-exit thinnings which are boundary conditions in FEM stamping simulation employing the linear multiple regression method by which the deviation of drawing characteristics between drawing test and mathematical model is minimized. In order to show the efficiency and accuracy of an expert drawbead model a finite element simulation of auto-body panel stamping is carried out. The finite element simulation shows that the expert drawbead model provides the accurate solution guarantees the stable convergence and the merit in the computation time.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.355-362
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• 2019

The aim of this study was to identify factors affecting life satisfaction for adolescents with asthma or atopic dermatitis. Korean Child and Youth Panel Survey (KCYPS) Data in 2016 was used. The data were analyzed by Chi-square test, t-test, one-way ANOVA and stepwise multiple linear regression. In multiple stepwise regression analysis, less depression, higher resilience, higher self-esteem, more affectionate parenting behavior, lower age enhances the life satisfaction of adolescents with allergic disease. Educational program is necessary to improve the life satisfaction of adolescents with asthma or atopic dermatitis which is reflecting the result of this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.283-290
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• 2020

The purpose of this study was to investigate the potential causal relationship between unmet healthcare needs and metrics related to quality of life. To examine the relationships between these variables, the study conducted an analysis by processing additional irradiated raw materials of the Korean Medical Panel. The metrics related to quality of life included six variables: athletic ability, self-care, daily activities, pain/trouble, uneasiness/depression, and subjective health conditions. Linear regression analysis revealed that the unmet healthcare needs had statistically significant negative effects on all six quality of life variables. A review of the magnitude of the linear regression β values for those variables showed that the relative level of influence on the quality of life variables decreased in the following order: pain/trouble, subjective health conditions, uneasiness/depression, daily activities, athletic ability, and self-care. Based on the results, practical applications related to strengthening working-level links between health and welfare is considered an effective policy response to the continued presence of unmet healthcare needs; such applications could contribute to improving the quality of life of those with unmet healthcare needs.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Korea Journal of Hospital Management
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• v.24 no.2
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• pp.1-11
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• 2019

Purpose: The purpose of this study is to identify relationship between work unstability and personal medical expenditure ratio focusing on wage workers' contract period. Method: This study analyzed 2015 yearly data beta version of Korea Health Panel, co-managed by Korea Institute for Health and Social Affairs and National Insurance Corporation for data analysis. When executing linear regression, Household income was applied with equivalized income, and the proportion of personal medical expenditure was naturally logged to perform linear regression and the demographic and socioeconomic factors were taken into account. The demographic and socio-economic factors were also considered. Findings: As a result of reviewing the used factors, it was found that the more unstable work status, the higher personal medical expenditure ratio. This result corresponds to 'The Theory of Fundamental Causes' by Link & Phelan. Conclusion : It indicates that policy efforts should be made to improve the working environment and health level of socially unstable workers.