• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.377-380
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• 1998

본 논문에서는 최근 데이터마이닝의 도구로 활발하게 소개되고 있는 의사결정나무 분석을 이용하여 개인휴대통신의 해지자 분석을 실시한다. 또한 로지스틱 회귀모형을 이용하여 가입고객의 해지 가능성에 대한 점수화를 시도한다.

• The Journal of Engineering Geology
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• v.14 no.4 s.41
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• pp.443-450
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• 2004

This study developed a prediction model of debris flow to predict a landslide probability on natural terrain composed of the Tertiary sedimentary and volcanic rocks using a logistic regression analysis. The landslides data were collected around Pohang, Gyeongbuk province where more than 100 landslides were occurred in 1998. Considered with basic characteristics of the logistic regression analysis, field survey and laboratory soil tests were performed for both slided points and not-slided points. The final iufluential factors on landslides were selected as six factors by the logistic regression analysis. The six factors are composed of two topographic factors and four geologic factors. The developed landslide prediction model has more than $90\%$ of prediction accuracy. Therefore, it is possible to make probabilistic and quantitative prediction of landslide occurrence using the developed model in this study area as well as the previously developed model for metamorphic and granitic rocks.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.321-328
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• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1137-1143
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• 2011

The purpose of this paper is to analyse the preference for direct marketing according to the characteristics of policyholders and suggest implications for marketing strategies with regard to direct marketing. A marked characteristic of this paper is a good quality of data and the results gained from analysing the data can be trusted very much. Binary logistic regression is employed. A statistically significant preference is shown in the group such as male, a younger generation, a hazardous occupation, the metropolitan area, and the customer of foreign company. The results suggest that promotion for female is needed to revitalize direct marketing. A tight underwriting for a hazardous occupation is also required.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.223-236
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• 2013

Various statistical classification methods to predict election to the Major League Baseball hall of fame of are implemented and their accuracies are compared. Seventeen independent variables are selected from the data of candidates eligible for the hall of fame and well-known classification methods such as discriminant analysis and logistic regression as well as the recently proposed Mahalanobis-Taguchi system(MTS). The MTS showed a better performance than the others in classification accuracy because it is especially efficient in cases where multivariate data does not constitute directionally geographical groups according to attributes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.15-31
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• 2024

The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.149-160
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• 2009

The purpose of this study is to comparatively analyse the behavior patterns of the first and the repeated offenders in DWI, and to develope the models of BAC(Blood Alcohol Concentration) by using multiple regression analysis method and a model of repeated DWI conviction by using logistic regression analysis method. The main results are as follows. First, the repeated offenders are more in criminal and traffic accidents records than that of the first offenders. The unlicenced drivers are in higher BAC than licenced drivers. Second, multiple regression model of BAC was developed, and the model revealed that criminal records and driving distance were important factors. Third, a model of repeated DWI conviction was developed, and the model revealed that traffic accidents records, whether or not having licence, and criminal records were most important factors.

• Survey Research
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• v.12 no.3
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• pp.173-186
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• 2011

We introduced the methodologies used to construct the longitudinal weights and cross-sectional weight that are required for the analysis of Korea Youth Panel Survey. To analyze the longitudinal dynamic change of the population, we derived the longitudinal weight through nonresponse adjustment based on logistic regression and post-stratification. Cross-sectional weights that are necessary to produce an asymptotically unbiased estimator of the population parameter were constructed through simple nonresponse adjustment based on overall response rate and post-stratification.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.492-492
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• 2021

최근 세계적으로 기상이변에 의해 한파와 폭설이 발생하고 있으며, 이로 인한 피해를 예측하기 어려워 졌다. 우리나라의 대설피해는 지역별로 상이해 강설 특성을 파악하기 위해 강설자료와 과거의 기상현상자료를 분석하여야 한다. 대표적인 대설피해로 설압피해, 적설피해, 착설피해와 간접피해로 분류 되며 시설재배면적에 가장 많은 영향을 미치는 설압피해는 쌓인 눈의 압력으로 인하여 파손 및 붕괴를 유발한다. 본 연구에서는 과거 재해연보 자료(1994년~2018년)와 기상청에서 제공되는 적설자료를 활용해 대설피해 관련 자료를 수집 및 분석하여 온실에 손상을 입힐 수 있는 적설심을 분석하였다. 로지스틱 회귀분석을 위한 자료 구축은 재해연보의 피해기간을 기반으로 하여 종속변수로 사용하였다. 이후 적설심자료를 최심신적설로 변형하였으며 온도와 함께 독립변수로 사용하였다. 우리나라의 대설 사례가 많은 영동지역은 강설빈도가 높아 대설 방지대책 및 대설 연구자료가 다른 지역에 비해 많은 것으로 판단된다. 이에 따라 최근 빈도가 증가하고 있으며 대설피해 사례가 10건 이상이고 관측지점이 피해지역과 가까운 지역, 적설관측자료가 연속적으로 관측되어 있는 남원, 보령, 장수, 부안을 공간적 범위로 선정하였다. 연구의 결과로 대설 피해 재난관리가 가능한 적설심 기준 설립에 도움을 줄 것으로 판단된다.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.101-105
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• 2005

호남지역에 대한 대설특보 예보를 위한 통계모형 개발을 수행하였다. 일 신적설량에 따라 세법주(0: 비발생, 1: 대설주의보, 2: 대설경보)로 구분되는 순서형 자료 형태를 지니고 있다. 두가지 통계 모형(다등급 로지스틱 회귀모형, 신경회로망 모형)을 고려하였으며, 수치모델 출력자료를 이용한 역학-통계모형 기법의 하나인 MOS(model output statistics)를 적용하여 축적된 수치모델 예보자료와 관측치의 관계를 통계모형식으로 추정하여 예측모형을 개발하였다. 군집분석을 사용하여 훈련자료와 검증자료를 구분하였으며, 예보치 생성을 위하여 문턱치를 고려하였다.