• Journal of the Korean Statistical Society
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• v.12 no.2
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• pp.81-90
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• 1983

The least squares estimator of disturbance variance in a regression model is biased under a serial correlation. Under the assumption of an AR(I), Theil(1971) crudely related the bias with the autocorrelation of the disturbances and the autocorrelation of the explanatory variable for a simple regression. In this paper we derive a relation which relates the bias with the autocorrelation of disturbances and the autocorrelation of explanatory variables for a multiple regression with improved precision.

• Korean Journal of Human Ecology
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• v.16 no.5
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• pp.1041-1050
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• 2007

The purpose of this study was to investigate the variables which had effects on deit behavior of male and female high school students. The proposed variables are their body-related variables(body satisfaction, weight control experience, the degree of diet interest, and obesity) and self-esteem. The sample group used for the study consisted of 359 high school students(male=168, female=191). Measurement scales used for the study were those of body-related variables, self esteem and eating disorder behavior, and data analysis was performed using $X^2$, t-test, Pearson's correlation, regression analysis. The results are as follows. First, there is a significant difference between male and female high school students regarding their obesity perceived by themselves, body satisfaction, the degree of diet interest, weight control experience, and deit behavior. Second, In male students, diet behavior shows a positive correlation with the degree of diet interest, weight control experience, and body satisfaction, but shows a negative correlation with body satisfaction. In female students, diet behavior is positively correlated with the degree of diet interest, weight control experience, and obesity, but negatively correlated with body satisfaction and self-esteem. Third, in male students, the variables that showed a influence on diet behavior as an eating disorder are weight control experience, body satisfaction and obesity, in that the explanatory power of the variables is 51.7% with the highest mark on obesity. In female, the variables that showed a influence on diet behavior as an eating disorder are the degree of diet interest, weight control experience, body satisfaction and obesity, in that the explanatory power of the variables is 66.0%.

• Journal of Environmental Science International
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• v.25 no.2
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• pp.191-216
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• 2016

Since prolonged exposure to elevated ozone ($O_3$) concentrations is known to be harmful to human health, appropriate control strategies for ozone are needed for the non-attainment area such as Seoul, Korea. The goal of this research is to assess factors linked with the 1-hour ozone exceedance through a decision tree model. Since ozone is a secondary pollutant, lag times between ozone and explanatory variables for ozone formation are taken into account in the model to improve the accuracy of the simulation. Results show that while ozone concentrations of the previous day and $NO_2$ concentrations in the morning are major drivers for ozone exceedances in the early afternoon, meteorology plays more important role for ozone exceedances in the late afternoon. Results also show that a selection of lag times between ozone and explanatory variables affect the accuracy of predicting 1-hour ozone exceedances. The result analyzed in this study can be used for developing control strategies of ozone in Seoul, Korea.

• Asian Journal of Innovation and Policy
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• v.3 no.2
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• pp.193-215
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• 2014

This study analyzes the factors on the determinants of research productivity. In addition, this study uncovers the relationships between research productivity and various explanatory variables, and between explanatory variables. As for research productivity, 3 indices were used such as the number of papers, patents, and a combination of them. The data is the 3-year average from 2010-2012 by 1,383 researchers from 6 disciplines such as physics, chemistry, biology, mechanical engineering, electricity and electronics, and chemical engineering, reported to the National Research Foundation of Korea. Personal factors such as sex, age, academic rank and location of affiliation show the group difference for productivity. In addition, most resource factors such as the number of graduate students and research funds showed the same result with personal factors. As for the determinants, master and doctoral students and government funds are the most powerful factors for research productivity, but industry funds for patent and overall productivity.

• Journal of Korea Technology Innovation Society
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• v.1 no.3
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• pp.374-385
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• 1998

This study is estimates telephone service demand based on empirical studies of telecommunication service demand model. First, the telephone charge(call price index) by each location and subscription fee bring about a negative effect to telephone distribution rate: while the other explanatory variables bring about a positive effect. Second, the flexibility of telephone charge in A location(relevant location) and the flexibility between the distance of A location and B location are negative values, while the flexibility of other explanatory variables is represented in a positive value. This means that the long distance call numbers from A location to B location are in inverse proportion against the phone charge(call price index) of A location and against the distance between A location and the distance of other locations except A location, while they are in direct proportion with an average call number per minute from A location to other locations except A location, and also with subscription numbers of A location, other subscribers in locations other than A location, and the total expenditures of A location.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.227-233
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• 2004

This paper presents our work on constructing a model that is intended to predict the probability of attrition at specified points in time among customers of an insurance company. There are some difficulties in building a data-based model because a data set may contain possibly censored observations. In an effort to avoid such kind of problem, we performed logistic regression over specified time intervals while using explanatory variables to construct the proposed model. Then, we developed a Cox-type regression model for estimating the probability of attrition over a specified period of time using time-dependent explanatory variables subject to changes in value over the course of the observations.

• Journal of Family Resource Management and Policy Review
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• v.6 no.1
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• pp.103-115
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• 2002

The purpose of this study was to analyze which factor, influenced the business and family performance success. Data were obtained from 248 family households. Proxy variable of the business performance was gross business income and of the family performance was the Family AFGAR scores. The multiple regression analysis was conducted for both the business performance equation and family performance equation. The main results of this study were as followings: The results indicated the effects of various business and family characteristics on performance and their contributions to the business and family performance model. Nine explanatory variables such as sex, being home-based, number of hours worked per week, number of family employee, number of nonfamily employee, total asset, the presence of young child under 6, nonbusiness income, and role conflicts were statistically significant in the business performance equation and three explanatory variables such as the hours worked per week, family stress scores, and role conflicts were statistically significant in the family performance equation. The results indicated the need for a more comprehensive view of family business performance.

• Korean Journal of Organic Agriculture
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• v.22 no.3
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• pp.397-412
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• 2014

This study estimated reasonable rental for Kleingarten (weekend farm) in Kyungpook province. To estimate Willingness To Pay (WTP) for Kleingarten rental, a survey was committed for the aged 20 and above who live in Daegu area. Through the Single Bounded Dichotomous Choice (SBDC) method, WTPs were estimated from 338,361 won to 357,646 won. Explanatory variables are leisure frequency, state of retirement, intention to get Kleingarten, sex and income levels and so on. As we expected, all explanatory variables are positively related with WTP.

• Journal of Korean Society of Forest Science
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• v.95 no.5
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• pp.601-604
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• 2006

This study compared the accuracy of partial multivariate and vector autoregressive models for lumber demand prediction in Korea. The partial multivariate model has three explanatory variables; own price, construction permit area and dummy. The dummy variable reflected the boom of lumber demand in 1988, and the abrupt decrease in 1998. The VAR model consists of two endogenous variables, lumber demand and construction permit area with one lag. On the other hand, the prediction accuracy was estimated by Root Mean Squared Error. The results showed that the estimation by partial multivariate and vector autoregressive model showed similar explanatory power, and the prediction accuracy was similar in the case of using partial multivariate and vector autoregressive model.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.491-498
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• 2013

We consider support vector machines(SVM) to predict Y with p numerical variables $X_1$, ${\ldots}$, $X_p$. This paper aims to build a biplot of p explanatory variables, in which the first dimension indicates the direction of SVM classification and/or regression fits. We use the geometric scheme of kernel principal component analysis adapted to map n observations on the two-dimensional projection plane of which one axis is determined by a SVM model a priori.