• The Korean Journal of Applied Statistics
• /
• v.21 no.1
• /
• pp.151-157
• /
• 2008

In generally, we use a method of the survey to forecast the economic demands and non-economic demands for a market trend. But we have a difficult problem to estimate the demand for the marketplace objectively because the survey with the non-response and the inadequate understanding on questionnaires did not provided the strong and uniform forecast. Here, we proposed a method compounded of survey and a statistical model to estimate the demand for the marketplace and discussed the mixture model applied to the service demand on an agency.

• International Journal of Highway Engineering
• /
• v.11 no.2
• /
• pp.17-25
• /
• 2009

The goal of this study is to develop Logistic regression model by accident location(entry section, exit section, inside intersection and pedestrian crossing section). Based on the accident data of Chungbuk Provincial Police Agency(2004$\sim$2005) and the field survey data, the geometric elements, environmental factor and others related to traffic accidents were analyzed. Developed models are all analyzed to be statistically significant(chi-square p=0.000, Nagelkerke $R^2$=0.363$\sim$0.819). The models show that the common factors of accidents are the traffic volume(ADT), distant of crossing and exclusive left turn lane, and the specific factors are the minor traffic volume(inside intersection model) and U-turn of main road(pedestrian crossing model). Hosmer & Loineshow tests are evaluated to be statistically significant(p$\geqq$0.05) except the entry section model. The correct classification rates are also analyzed to be very predictable(more than 73.9% to all models).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.4
• /
• pp.327-335
• /
• 2019

This study develops a prediction model for toilet and laundry water end-uses based on surveyed data which measured housing and household characteristics of 140 households over 5 years in Korea. Classical regression model assuming a normal distribution was not appropriate and estimated parameters were biased, because the distribution of measured water-uses was left-skewed. As an alternative to this problem, we considered the distribution of weibull and lognormal for each water-uses, and three regression models were compared using log-likelihood and scale parameter. As a result, weibull regression were chosen to be appropriate for both water-uses and also presented the factors that affect each water-use. This results expect that an insight is provided on water resources utilization and theoretical support role for effective water resource management.

• Proceedings of the Korean Association for Survey Research Conference
• /
• 2006.12a
• /
• pp.41-47
• /
• 2006

통계청은 1999과 2004년 두 차례에 걸쳐 '생활시간조사(Time Use Survey)'를 실시한 바 있다. 이 조사는 우리나라 국민이 하루 24시간을 어떠한 이용 행태로 시간 사용을 하고 있는 지를 조사함으로써 오늘의 국민들의 평균적인 생활방식과 삶의 질을 파악하고, 시간자원의 효율적 활용에 필요한 기초자료를 제공하는데 그 의의를 두고 있다. 특히 생활시간조사는 각 개인의 시간별 활동내용 뿐 아니라 개인의 여러 가지 인구통계학적 특성들을 함께 조사함으로써 이와 관련된 실증적 연구를 가능하게 한다. 본 연구에서 관심을 가지고 살펴보고자 하는 것은 개인의 생활시간소비 행태는 성별 및 사회적 역할과 연관되어 있다고 생각되기 때문이다. 특히 개인의 피로도의 정도와 생활시간 소비 형태와의 관련성에 초점을 두고 로지스틱 회귀, 대응분석을 통하여 살펴보고자 한다.

• Communications for Statistical Applications and Methods
• /
• v.5 no.3
• /
• pp.803-808
• /
• 1998

본 논문에서는 국제전화 수요에 영향을 주는 거시경제 변수를 조사하여, 관계를 판명하고, 특히 국제전화 요금이 수요에 미치는 영향을 밝힐 수 있는 요금탄력성 계수를 추정하는 것이 목적이다. 우리는 오차의 자기상관을 고려한 회귀분석 모형을 이용하였다.

• Survey Research
• /
• v.12 no.3
• /
• pp.49-62
• /
• 2011

In this paper we investigate design-based properties of both the ordinary least square estimator and the weighted least square estimator for regression coefficients in panel regression model. We derive formulas of approximate bias, variance and mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator after linearization of least square estimators. Also we compare their magnitudes each other numerically through a simulation study. We consider a three years data of Korean Welfare Panel Study as a finite population and take household income as a dependent variable and choose 7 exploratory variables related household as independent variables in panel regression model. Then we calculate approximate bias, variance, mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator based on several sample sizes from 50 to 1,000 by 50. Through the simulation study we found some tendencies as follows. First, the mean square error of the ordinary least square estimator is getting larger than the variance of the weighted least square estimator as sample sizes increase. Next, the magnitude of mean square error of the ordinary least square estimator is depending on the magnitude of the bias of the estimator, which is large when the bias is large. Finally, with regard to approximate variance, variances of the ordinary least square estimator are smaller than those of the weighted least square estimator in many cases in the simulation.

• The Journal of Korean Association of Computer Education
• /
• v.16 no.2
• /
• pp.39-48
• /
• 2013

This study investigates the predictive model of the adolescents' computer entertainment behavior using neural network with the KYPS data (3449 in the junior high school; 1725 boys and 1724 girls). This study compares the results of neural network(model 1) to the logistic regression model and neural network(model 2) with the exact same variables used in logistic regression. The results reveal that the prediction of neural network model 1 is the highest among three models and with gender, computer use time, family income, the number of close friends, the number of misdeed friends, individual study time, self-control, private education time, leisure time, self-belief, stress, adaptation to school, and study related worries, the neural network model 1 predicts the computer entertainment behavior more efficiently. These results suggest that the neural network could be used for diagnosing and adjusting the adolescents' computer entertainment behavior.

• Journal of Korean Society of Transportation
• /
• v.22 no.3 s.74
• /
• pp.127-135
• /
• 2004

교차로 안전성 진단과 관련된 기존의 연구는 교차로 상에서 발생한 사고 자료에 기초하여 교차로 기하구조 요소, 교통량 및 신호운영방법 등과 관련된 요인을 변수로 사용하여 교통사고건수 예측모형 개발에 관한 연구가 대부분이다. 그러나, 분석하고자 하는 대상 교차로의 사고건수 예측모형을 개발하기 위해 필요한 교통사고 자료의 경우 단 기일에 걸쳐 획득되지 않으며 몇 년간의 사고 자료를 요구할 수도 있다. 이러한 자료를 이용하더라도 사고 발생 기간동안 교차로 사고에 영향을 미치는 요인(교차로 운영방법, 기하구조 등)이 변화될 수도 있다는 문제점을 지닌다. 이와 같은 이유로 교차로 안전성을 진단하는데 있어 기존 교통사고 자료는 언제나 절대적인 자료가 될 수 없다. 이에 대한 보완책으로, 3일에서 5일정도의 조사 자료만으로도 안전성 진단이 가능한 상충자료를 이용하여 교차로 안전성 진단을 할 수 있다. 본 연구는 기존사고 자료를 이용하여 사고 발생에 기인하는 여러 변수들을 교통사고심각도와의 상관관계를 분석하고, 상관관계가 높은 변수를 이용하여 신경망 사고심각도 예측모형을 개발하였으며, 모형 검증을 위해 다중회귀사고심각도 예측모형을 개발하여 비교 평가한 결과 신경망 사고심각도 예측모형의 예측력이 우수한 것으로 나타났다. 현장에서 조사된 상충자료를 신경망 사고심각도 예측모형에 적용하여 상충이 사고로 연결 될 경우 사고심각도를 예측하였으며, 예측된 사고심각도에 가중치를 부여하여 대상 교차로 위험우선순위를 결정한 결과 사고비용에 기초한 위험우선순위 결정법과 같은 순위의 결과를 도출하였다.

• Journal of Digital Convergence
• /
• v.11 no.9
• /
• pp.255-265
• /
• 2013

The purpose of this study was to identify the variation factors of hypertension medication rate between regions and to use them as a basic data for establishment of hypertension management business plan which is customized by region. The data were collected from community health survey, National Statistics Office and National Health Insurance Corporation, and were analyzed using the geographically weighted regression. As the result of analysis, the factors that influenced the hypertension medication rate between regions were subjective recognition rate of health level, the rate of medical aid client and the number of health facility per one hundred thousand of population. According to the geographically weighted regression, the total of 230 regional regression models composed of major variables which affected the hypertension medication rate were calculated. However, this study has several limitations that the explanatory power of model is not high and others. Therefore, a follow-up study which is based on the actual data of compliance with hypertension medication will be necessary.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1337-1348
• /
• 2017

In this paper, we develop the high-risk drinking predictive model in Korea using the cross-sectional data from Korea Community Health Survey (2014). We perform the logistic regression analysis, the decision tree analysis, and the neural network analysis using the data mining technique. The results of logistic regression analysis showed that men in their forties had a high risk and the risk of office workers and sales workers were high. Especially, current smokers had higher risk of high-risk drinking. Neural network analysis and logistic regression were the most significant in terms of AUROC (area under a receiver operation characteristic curve) among the three models. The high-risk drinking predictive model developed in this study and the selection method of the high-risk intensive drinking group can be the basis for providing more effective health care services such as hazardous drinking prevention education, and improvement of drinking program.