• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.293-300
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• 2012

When Binomial data are obtained, logit and logit mixed models are commonly used for small area estimation. Those models are known to have good statistical properties through the use of unit level information; however, data should be obtained as area level in order to use area level information such as spatial correlation or auto-correlation. In this research, we suggested a new small area estimator obtained through the combination of unit level information with area level information.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.201-210
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• 2020

Baseline-category logit random effects models have been used to analyze longitudinal nominal data. The models account for subject-specific variations using random effects. However, the random effects covariance matrix in the models needs to explain subject-specific variations as well as serial correlations for nominal outcomes. In order to satisfy them, the covariance matrix must be heterogeneous and high-dimensional. However, it is difficult to estimate the random effects covariance matrix due to its high dimensionality and positive-definiteness. In this paper, we exploit the modified Cholesky decomposition to estimate the high-dimensional heterogeneous random effects covariance matrix. Bayesian methodology is proposed to estimate parameters of interest. The proposed methods are illustrated with real data from the McKinney Homeless Research Project.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.61-77
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• 1995

The main objective of this research is the development of a logit model of urban workers' auto ownership choice. For the utility specification. a variety of behavioral hypotheses about the factors which affect the urban workers' auto ownership choice are considered. Based on the behavioral hypotheses, a binary logit model of auto ownership is estimated. Empirical estimation is based on a sample of workers taken in Daegu City(1994). The binary logit model of auto ownership development in this paper provides reasonable results in terms of behavioral and statistical considerations. Furthermore, this paper develops several submarket models of auto ownership choice. Market segmentation was made using age, sex, income, home-to-work time distance. It is found that the estimated results with market segmentation are also reasonable. Finally future directions of model development are suggested.

• Journal of the Korean Institute of Landscape Architecture
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• v.16 no.3
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• pp.1-6
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• 1989

The current linear programming model as for city park planning has the following intrinsic constraints. First of all, it cannot explicity consider choice behaviors of people. Secondly, the objective function of linear programming model cannot sufficiently intergrate satisfactions of people. In order to overcome these weak points of linear programming model, the following extensions have been made in this paper. First of all, bionominal and multinominal logit models based upon logit models, utility maximization of people have been constructed, Secondly, based upon logit models, social welfare function has been constructed in order to aggregate satisfactions of people. By doing this, intrinsic oonstraints of linear programming model have been successfully overcome. In the future research, empirical study of the model developed in this paper will be necessary. By doing this, the construction of optimal investment plan for city parks will be possible.

• International Journal of Contents
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• v.10 no.4
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• pp.75-82
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• 2014

The purpose of this paper was to identify suitable variables for financial distress prediction models and to compare the accuracy of MDA and LA for early warning signals for wind energy companies in Korea. The research methods, discriminant analysis and logit analysis have been widely used. The data set consisted of 15 wind energy SMEs in KOSDAQ with financial statements in 2012 from KIS-Value. We found that five financial ratio variables were statistically significant and the accuracy of MDA was 86%, while that of LA is 100%. The importance of this study is that it demonstrates empirically that financial distress prediction models are applicable to the wind energy industry in Korea as an early warning signs of impending bankruptcy.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.55-70
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• 2001

Artificial neural network(ANN) models have been widely used for the classification problems in business such as bankruptcy prediction, credit evaluation, etc. Although the application of ANN to classification of consumers＇ choice behavior is a promising research area, there have been only a few researches. In general, most of the researches have reported that the classification performance of the ANN models were better than conventional statistical model Because the survey data on consumer behavior may include much noise and missing data, ANN model will be more robust than conventional statistical models welch need various assumptions. The purpose of this paper is to study the potential of the ANN model for forecasting consumers＇ choice behavior based on survey data. The data was collected by questionnaires to the shoppers of department stores and discount stores. Then the correct classification rates of the ANN models for the training and test sample with that of multiple discriminant analysis(MDA) and logistic regression(Logit) model. The performance of the ANN models were betted than the performance of the MDA and Logit model with respect to correct classification rate. By using input variables identified as significant in the stepwise MDA, the performance of the ANN models were improved.

• International Journal of Highway Engineering
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• v.16 no.4
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• pp.111-118
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• 2014

PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.461-469
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• 2015

The next generation high-speed train, HEMU-430X, was developed and is now being tested. However, the existing mode choice models based on the guidelines for feasibility studies do not consider a high-speed train with a higher speed than KTX. This limitation might result in inaccurate demand forecasting. In this research, a stated preference survey was conducted in order to supplement the problem by considering the characteristics of HEMU-430X. Based on the survey results, this research developed two mode choice models, including a multinomial logit model and a nested logit model. For this purpose, the utility functions of travel time and travel costs were estimated using a Limdep 8.0 NLOGIT 3.0 package. After comparing the two models, it was concluded that the nested logit model is appropriate. The paper suggested a plan to implement the nested logit model and presented a policy implication.

• Journal of Korean Society of Rural Planning
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• v.17 no.1
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• pp.59-65
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• 2011

Re-visitation have an effect on dependent variables of regional tourism demand model. This study focused on the re-visitation impacts of consideration on sustainable tourism development of tourists as a new factors of tourism. Based on literature reviews, 11 variables were selected, a questionnaire survey was given to 406 tourists divided into 5 tourism sites at Chuncheon city, and logit model and probit model were used for analysis. The fitness levels of two models were very significant(p=0.0000). The study results suggest that the likelihood of the rural tourist to make a return visit is influenced by recognition of sustainable tourism, purchase of souvenir and farm produce, visitation of regional shops, conversation with regional residents, residents' participation on development, age and marriage. The results of such re-visitation demand can provide information for regional development strategies. The approach to re-visitation research impacts of consideration on sustainable tourism development is expected to become a useful foundation in studying on sustainable regional development.