• Communications of the Korean Mathematical Society
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• v.31 no.1
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• pp.185-198
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• 2016

Regression analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variable and response variables. This paper propose a fuzzy regression analysis applying Theils method which is not sensitive to outliers. This method use medians of rate of increment based on randomly chosen pairs of each components of ${\alpha}$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. An example and two simulation results are given to show fuzzy Theils estimator is more robust than the fuzzy least squares estimator.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.1-9
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• 2010

This paper suggests a mixed-effects model for analyzing split-plot data when there is a repeated measures factor that affects on the response variable. Covariance structures are discussed among the observations because of the assumption of a repeated measures factor as one of explanatory variables. As a plausible covariance structure, compound symmetric covariance structure is assumed for analyzing data. The restricted maximum likelihood (REML)method is used for estimating fixed effects in the model.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.116-130
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• 2003

The gap-based SERVQUAL model is a popular service quality determinant due to its superior diagnostic capacity over alternative explanatory frameworks. However, some researchers criticize the performance of the SERVQUAL model and propose alternative service Quality measurement constructs. Nevertheless, it is argued that the superior diagnostic capacity of SERVQUAL is its key strength; and that any criticism made of it when making comparison with alternative models does not reflect the differing nature of scales of statistical analysis. Arguably, the only limitation of a gap-based model is misinterpretation of customers' evaluation and perception of a service. In this research, the gap score is transformed into a ratio score. Also, empirical tests and implications are presented to support this alternative contribution to the body of knowledge.

• Journal of the Korean Regional Science Association
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• v.14 no.2
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• pp.35-50
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• 1998

This paper examines the determinants of imbalanced regional development in Korea during the period of 1985-1995. The review of previous analytical techniques have been used to analyze the determinants of disparities in regional development of disparities in regional development, but few has applied the regression technique which reduces a bias due to heterogeneity across region. The results of the study show that Kmenta model with per capita GRDP as dependent variable can reduce the heterogeneity bias in regional development and can minimize the statical errors in estimation and interpretation of the coefficients of the explanatory variables. According to the results of Kmenta model, urban infrastructure such as roads, information and communication facilities are major causes of regional disparity over the period of 1985-1995. The results of the study also indicate that local government should devote their policy efforts to identify and utilize the unique soci-economic characteristics of each locality in the process of regional development.

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

• Journal of the Korean Regional Science Association
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• v.10 no.2
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• pp.61-71
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• 1994

Despite of being the criteria to choose the efficient and reasonable alternatioves inactual planning process, the measure of accessibility rarely has applied to practices because each model has unexplicity concept of it and limitations in itself. Accessibility implies transportation system which offers opportunity of movement to overcome spatial separation and, simultaneously, land-use system which represents the location of each activity. Therefore, measures of accessibility have to represent the attractiveness of locations and the interactions of activities, that is, land-use and transportation, with an index. Considering that urban activity is based on the economic efficiency, costs and benfits, accessibility means the economic efficiency of the location of activity and the travel in view of land-use and transport repectively. Combined models that measure accessibility with considering land-use and tranportation simultaneously depend on reasonable concepts, but it is too simple for them to explain the accessibility which resulted from complex interaction of urban activities. Combined urban activity model developed by Kim (1983) and Rho (1989) explains the characteristics of activities in each regions and urban strcture in economic general equilibrium states in the long term of urban system. This model measures a regional accessibility with a dual variable which means the location surplus. This is a more systematic and comprehensive model for calculating the regional accessibility because it considers the interaction of each activity in urban system. It needs efforts to apply the accessibility index as a criterion in actual planning process through finding and quantitification of other explanatory variables to measure it in combined urban activity model.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.149-169
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• 2015

This study tried to find out how to overcome multicollinearity problems in the structural equation model by creating a hierarchical construct model about the repurchase intention of social commerce. This study selected, as independent variables, price, quality, service, and social influence, based on literature review about social commerce, and then, as detailed variables of independent variables, selected system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norms, and reputation. As results of empirical analysis about hierarchical construct model, all the independent variables were accepted having a significant impact on repurchase intention of social commerce. Next, this study analyzed the competition model that eight independent variables of price, system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norm, and reputation directly influence the repurchase intention of social commerce. As results of empirical analysis, system quality, information quality, transaction safety, communication appeared to be insignificant. This study showed that hierarchical construct model is useful to overcome the multicollinearity problem in structural equational model and to increase explanatory power.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.125-160
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• 2007

Data Warehousing and OLAP (On-Line Analytical Processing) have turned into the key technology for comprehensive data analysis. Originally developed for the needs of decision support in business, data warehouses have proven to be an adequate solution for a variety of non-business applications and domains, such as government, research, and medicine. Analytical power of the OLAP technology comes from its underlying multidimensional data model, which allows users to see data from different perspectives. However, this model displays a number of deficiencies when applied to non-conventional scenarios and analysis tasks. This paper presents an attempt to systematically summarize various extensions of the original multidimensional data model that have been proposed by researchers and practitioners in the recent years. Presented concepts are arranged into a formal classification consisting of fact types, factual and fact-dimensional relationships, and dimension types, supplied with explanatory examples from real-world usage scenarios. Both the static elements of the model, such as types of fact and dimension hierarchy schemes, and dynamic features, such as support for advanced operators and derived elements. We also propose a semantically rich graphical notation called X-DFM that extends the popular Dimensional Fact Model by refining and modifying the set of constructs as to make it coherent with the formal model. An evaluation of our framework against a set of common modeling requirements summarizes the contribution.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.325-336
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• 2019

In this article we extend the discrete Weibull regression model in the presence of missing data. Discrete Weibull regression models can be adapted to various type of dispersion data however, it is not widely used. Recently Yoo (Journal of the Korean Data and Information Science Society, 30, 11-22, 2019) adapted the discrete Weibull regression model using single imputation. We extend their studies by using multiple imputation also with several various settings and compare the results. The purpose of this study is to address the merit of using multiple imputation in the presence of missing data in discrete count data. We analyzed the seventh Korean National Health and Nutrition Examination Survey (KNHANES VII), from 2016 to assess the factors influencing the variable, 1 month hospital stay, and we compared the results using discrete Weibull regression model with those of Poisson, negative Binomial and zero-inflated Poisson regression models, which are widely used in count data analyses. The results showed that the discrete Weibull regression model using multiple imputation provided the best fit. We also performed simulation studies to show the accuracy of the discrete Weibull regression using multiple imputation given both under- and over-dispersed distribution, as well as varying missing rates and sample size. Sensitivity analysis showed the influence of mis-specification and the robustness of the discrete Weibull model. Using imputation with discrete Weibull regression to analyze discrete data will increase explanatory power and is widely applicable to various types of dispersion data with a unified model.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.523-534
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• 2016

The purpose of this study is to develope a method for measuring social benefit by mitigating in-vehicle congestion level in intercity buses. Contingent valuation method and Tobit model are adopted for social benefit evaluation method. One thousand passengers were interviewed with 992 obtained valid samples. Tobit models with age, income level, and bus boarding times as explanatory variables are selected to estimate the willingness to pay for the mitigation of intercity bus in-vehicle congestion. Statistically and logically, two models with age or income level as explanatory variables are turned out to be valid. The intercity bus service supply status and usage are examined and the bus users who have willingness-to-pay for the intercity bus in-vehicle congestion mitigation have been identified. In case of the 'no standing' rules implemented to the intercity bus, the annual economic benefit from the service is estimated to be 14.7 billion won.