• Journal of the Korean Data and Information Science Society
• /
• v.24 no.1
• /
• pp.85-94
• /
• 2013

As the financial market becomes larger, the loss increases due to the failure of the credit risk managements from the poor management of the customer information or poor decision-making. Thus, the credit risk management also becomes more important and it is essential to develop a credit scoring model, which is a fundamental tool used to minimize the credit risk. Credit scoring models have been studied and developed only for binary target variables. In this paper, we consider other types of target variables such as ordinal multinomial data or longitudinal binary data and suggest credit scoring models. We then apply our developed models to real data and random data, and investigate their performance through Kolmogorov-Smirnov statistic.

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

• Communications for Statistical Applications and Methods
• /
• v.21 no.4
• /
• pp.275-284
• /
• 2014

Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.

• Industrial Engineering and Management Systems
• /
• v.1 no.1
• /
• pp.73-78
• /
• 2002

In this paper, we propose a constrained optimization model for conjoint analysis (a preference decomposition technique) to improve parameter estimation by restricting the relative importance of the attributes to an extent as decided by the respondents. Quite simply, respondents are asked to provide some pairwise attribute comparisons that are then incorporated as additional constraints in a linear programming model that estimates the partial preference values. This data collection method is typical in the analytic hierarchy process. Results of a simulation study show the new model can improve the predictive accuracy in partial value estimation by ordinal east squares (OLS) regression.

• The Korean Journal of Applied Statistics
• /
• v.25 no.2
• /
• pp.363-376
• /
• 2012

Excessive zeroes are often observed in ordinal categorical response variables. An ordinary ordered Probit model is not appropriate for zero-inflated data especially when there are many different sources of generating 0 observations. In this paper, we apply a two-stage zero-inflated ordered Probit (ZIOP) model which incorporate the zero-flated nature of data, propose a Bayesian analysis of a ZIOP model, and apply the method to alcohol consumption data collected by the National Bureau of Statistics, Korea. In the first stage of a ZIOP model, a Probit model is introduced to divide the non-drinkers into genuine non-drinkers who do not participate in drinking due to personal beliefs or permanent health problems and potential drinkers who did not drink at the time of the survey but have the potential to become drinkers. In the second stage, an ordered probit model is applied to drinkers that consists of zero-consumption potential drinkers and positive consumption drinkers. The analysis results show that about 30% of non-drinkers are genuine non-drinkers and hence the Korean alcohol consumption data has the feature of zero-inflated data. A study on the marginal effect of each explanatory variable shows that certain explanatory variables have effects on the genuine non-drinkers and potential drinkers in opposite directions, which may not be detected by an ordered Probit model.

• IE interfaces
• /
• v.15 no.2
• /
• pp.209-217
• /
• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.5
• /
• pp.685-692
• /
• 2018

Busan city implemented 'taxi transfer discount system' since October 2017 in order to create for new demand taxis. However, due to the low transfer discount amount and limited payment method to prepaid cards, it is difficult to attain the aim. In this study, we investigated the usage status of taxi transfer discount system and the intention to use taxi transfer discount system according to the discount amount level. We established a model of intention to estimate demand of taxi transfer discount using ordinal logistic model. The results of analysis are as following. The critical reason for low usage was to limit taxi transfer discount payment methods to prepaid cards other than post-paid cards which is used for most transportation payment. It was found that the discount rate for taxi transfers was affected in order of payment method, the purpose of the travel, major transportation, frequency taxi use, age, transportation costs, and the discount of taxi transfers. Also, the taxi transfer discount could be expected to increase to 1,550 won based on the price elasticity of demand due to changes in taxi transfer discount rate.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.3
• /
• pp.1-13
• /
• 2019

The study examines preference between rural bus and call-a-bus before call-a-bus operation and empirically analyzes the effecting factors on the call-a-bus satisfaction after operation. As the result of log-linear model, older persons prefer call-a-bus because of door-to-door service convenience and female also because of limitation of trip moving means. It is shown that persons with lower number of trips prefer call-a-bus. As the result of ordinal regression model for call-a-bus satisfaction, age, the number of family members and bus stop distance have the positive tendency but the going out frequency and the return time negative among rural bus preference persons. Male and the going out frequence show the negative tendency but trip moving means, bus stop distance, rural bus satisfaction, depart and return time positive among call-a-bus preference persons. The persons who have the positive preference on call-a-bus shows higher satisfaction on call-a-bus.

• Communications for Statistical Applications and Methods
• /
• v.15 no.4
• /
• pp.517-530
• /
• 2008

In this paper we introduce a time series model using the triangle fuzzy numbers in order to construct a statistical relation for the data which is a sequence of observations which are ordered in time. To estimate the proposed fuzzy model we split of a universal set includes all observation into closed intervals and determine a number and length of the closed interval by the frequency of events belong to the interval. Also we forecast the data by using a difference between observations when the fuzzified numbers equal at successive times. To investigate the efficiency of the proposed model we compare the ordinal and the fuzzy time series model using examples.

• Health Policy and Management
• /
• v.23 no.2
• /
• pp.145-151
• /
• 2013

Background: The objective of this study was to explore patient family's evaluation of emergency department (ED) service satisfaction and to compare these with ED staff perception of patient family's evaluation. Methods: Based on two surveys of the National Emergency Medical Center: the 2008 National Survey for Recognition and Satisfaction towards Emergency Medical Services and the 2008 Opinion Survey of Emergency Medical Service Providers, satisfaction gaps among physicians, nurses, and patient family were evaluated by Kruskal-Wallis tests and Wilcoxon-Mann-Whitney tests. Furthermore, the factors associated with satisfaction of emergency medical service were identified by ordinal logistic regression models. Results: There were statistically significant gaps among physicians, nurses, and patient family in overall satisfaction with ED visit, length of stay in ED, enough explanation, physicians/nurses kindness, and ED facilities. Age and income in the patient family model, the number of beds in hospital, job satisfaction and year of service in the physicians model, and the number of beds in hospital, job satisfaction and the number of patients per duty hour in the nurses model were statistically significant factors associated with evaluation/ perception of ED service satisfaction. Conclusion: Patient satisfaction is an important indicator of the quality of care and service delivery in the ED. To improve and understand satisfaction in ED service, a dyadic view of the evaluation of service quality and satisfaction-that is, from the perspectives of both the patient and the emergency medical service providers-should be concerned.