• 한국정보시스템학회지:정보시스템연구
• /
• 제18권3호
• /
• pp.375-399
• /
• 2009

In this study, we propose a integrated model of logistic regression, artificial neural networks, support vector machines(SVM), with case-based reasoning(CBR). To predict respondents in the direct marketing is the binary classification problem as like bankruptcy prediction, IDS, churn management and so on. To solve the binary problems, we employed logistic regression, artificial neural networks, SVM. and CBR. CBR is a problem-solving technique and shows significant promise for improving the effectiveness of complex and unstructured decision making, and we can obtain excellent results through CBR in this study. Experimental results show that the classification accuracy of integration model using CBR is superior to logistic regression, artificial neural networks and SVM. When we apply the customer response model to predict respondents in the direct marketing, we have to consider from the view point of profit/cost about the misclassification.

• Journal of Forest and Environmental Science
• /
• 제24권3호
• /
• pp.137-142
• /
• 2008

In this paper, we apply a logistic regression model to the data of snow damage on sugi (Cryptomeria japonica) occurred in Toyama prefecture (in Japan) in 2004 for estimating the risk probability. In order to specify the factors effecting snow damage, we apply a model selection procedure determining optimal subset of explanatory variables. In this process we consider the following 3 information criteria, 1) Akaike's information criterion, 2) Baysian information criterion, 3) Bias-corrected Akaike's information criterion. For the selected variables, we give a proper interpretation from the viewpoint of natural disaster.

• Communications for Statistical Applications and Methods
• /
• 제29권2호
• /
• pp.203-223
• /
• 2022

We propose a Bayesian approach to cumulative logistic regression model for the ordinal response based on the orthogonal principal components via singular value decomposition considering the multicollinearity among predictors. The advantage of the suggested method is considering dimension reduction and parameter estimation simultaneously. To evaluate the performance of the proposed model we conduct a simulation study with considering a high-dimensional and highly correlated explanatory matrix. Also, we fit the suggested method to a real data concerning sprout- and scab-damaged kernels of wheat and compare it to EM based proportional-odds logistic regression model. Compared to EM based methods, we argue that the proposed model works better for the highly correlated high-dimensional data with providing parameter estimates and provides good predictions.

• Communications for Statistical Applications and Methods
• /
• 제14권1호
• /
• pp.1-9
• /
• 2007

A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.

• 보건행정학회지
• /
• 제10권2호
• /
• pp.1-21
• /
• 2000

This study reviewde various parametic and nonparametic method for forexasting hospital closures in Korea. We compared multivariate discriminant analysis, multivartiate logistic regression, classfication and regression tree, and neural network method based on hit ratio of each model for forecasting hospital closure. Like other studies in the literture, neural metwork analysis showed highest average hit ratio. For policy and business purposes, we combined the four analytical method and constructed a foreasting model that can be easily used to predict the probabolity of hospital closure given financial information of a hospital.

• Communications for Statistical Applications and Methods
• /
• 제20권2호
• /
• pp.129-136
• /
• 2013

Linear regression is the most basic statistical model for exploring the relationship between a numerical response variable and several explanatory variables. Logistic regression secures the role of linear regression for the dichotomous response variable. In this paper, we propose a biplot-type display of the multivariate data guided by the linear regression and/or the logistic regression. The figures show the directional flow of the response variable as well as the interrelationship of explanatory variables.

• Journal of the Korean Statistical Society
• /
• 제36권4호
• /
• pp.457-469
• /
• 2007

Many procedures are available to identify a single outlier or an isolated influential point in linear regression and logistic regression. But the detection of influential points or multiple outliers is more difficult, owing to masking and swamping problems. The multiple outlier detection methods for logistic regression have not been studied from the points of direct procedure yet. In this paper we consider the direct methods for logistic regression by extending the $Pe\tilde{n}a$ and Yohai (1995) influence matrix algorithm. We define the influence matrix in logistic regression by using Cook's distance in logistic regression, and test multiple outliers by using the mean shift model. To show accuracy of the proposed multiple outlier detection algorithm, we simulate artificial data including multiple outliers with masking and swamping.

• 한국콘텐츠학회논문지
• /
• 제9권2호
• /
• pp.125-132
• /
• 2009

세계의 경제가 지식 기반 경제로 급변함에 따라 특허경쟁력을 강화하기 위한 노력을 다각적으로 실시하고 있다. 이러한 특허경쟁력을 강화하기 위해 일반적으로 해당 기술 분야에 대한 특허동향조사를 통해 다양한 분석을 하고 있지만 대부분 현재까지의 기술동향에 대한 자료를 통계적으로 표현하거나 핵심 기술에 대한 전문가의 정성분석을 포함하는 정도에 국한되고 있다. 따라서 본 논문에서는 제한적으로 활용되고 있는 특허정보를 이용하여 향후 기술 확산 형태를 예측해 보고자 한다. 이를 위해 일반적으로 많이 사용되고 있는 확산모형인 Bass 모형과 Logistic 모형을 통해 실험을 진행하였고, 각 모형의 성능을 평가하기 위해 MSE값과 MAPE값을 이용하였다. 입력데이터로는 NCW 정보보호기술과 관련된 특허데이터를 사용함으로써 기존 특허동향조사와 연계한 심화분석을 도출하였다. 실험결과 NCW 정보보호기술에 대한 확산을 예측하기 위한 모형은 Logistic 모형이 더 우수함을 알 수 있었으며, NCW 정보보호기술은 2008년 현재 점차 기술 성숙기에 접어들고 있음을 예측할 수 있었다.

• Journal of applied mathematics & informatics
• /
• 제9권2호
• /
• pp.459-517
• /
• 2002

The purpose of this paper is to provide a careful and accessible exposition of diffusive logistic equations with indefinite weights which model population dynamics in environments with strong spatial heterogeneity. We prove that the most favorable situations will occur if there is a relatively large favorable region (with good resources and without crowding effects) located some distance away from the boundary of the environment. Moreover we prove that a population will grow exponentially until limited by lack of available resources if the diffusion rate is below some critical value; this idea is generally credited to Thomas Malthus. On the other hand, if the diffusion rate is above this critical value, then the model obeys the logistic equation introduced by P. F. Verhulst .

• 한국유통학회지:유통연구
• /
• 제3권1호
• /
• pp.145-158
• /
• 1998

The selection of proposed sites for the general logistic center of agriculture products would be made the most suitable place by considering the spread of population as real consumers, the prospect of the demand, the expansion of traffic system, the regional, hourly and carring traffic volume and the use of land based urban planning, etc. As the preconsideration, the possible occupant companies have to be selected on the category of business and the district. After posing questions and having interview, several selected regions would be compared and analysed for deciding the most suitable place. The model for the general logistic center of agricultural products must be selected taking key factors approach for choosing key factors at first and referring to many documentary records. And the more, cooperating with the specialists for location selection and making objective questions to concerned companies, the most suitable place is selected by marking high score for the moderate land cost, the low traffic jam, the connection with the back cities and the possible expansion as the general logistic center of agriculture products.