• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2829-2840
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• 2018

The random variable with an arbitrary value or more is called semi-continuous variable or zero-inflated one in case that its boundary value is more frequently observed than expected. This means the boundary value is likely to be practically observed more than it should be theoretically under certain probability distribution. When the distribution considered is continuous, the variable is defined as semi-continuous and when one of discrete distribution is assumed for the variable, we regard it as zero-inflated. In this study, we introduce the two-part model, which consists of one part for modelling the binary response and the other part for modelling the variable greater than the boundary value. Especially, the zero-inflated regression models are explained by using Poisson distribution and negative binomial distribution. In real data analysis, we employ the zero-inflated regression models to estimate the number of days under extreme heat-wave circumstances during the last 10 years in South Korea. Based on the estimation results, we create prediction maps for the estimated number of days under heat-wave advisory and heat-wave warning by using the universal kriging, which is one of the spatial prediction methods.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.19-32
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• 2020

The purpose of this study was to investigate the influence factors of the university level centering on the entrepreneurial performance of the university students and full-time faculties in the situation of increasing interest in entrepreneurial university. In order to achieve the purpose of the study, a panel data was established from 2015 to 2018 on the basis of the university notification data. The panel data included universities with data on the number of university students and full-time faculty founders for at least two years. Through this, four year data from 154 universities were used for analysis. As an analysis method, frequency analysis and descriptive statistics were conducted to understand the characteristics of the university. Since then, panel negative binomial regression analysis has been conducted in consideration of the longitudinal features and distribution of the data. Also, based on the Hausman test results, the results were interpreted based on random effect model. The results of this study are as follows. First, as a result of the analysis of the entrepreneurial performance and the change trend of the domestic university from 2015 to 2018, the entrepreneurial performance of the university has been steadily increasing in the last four years, and the increase in the number of university student entrepreneurs was relatively higher than the full-time faculties. Second, economic and educational approaches need to be combined to promote university students' start-ups. The university factors that promote the start-up of university students were found to be scholarships, start-up grants, startup lectures, and startup clubs. Third, the openness and regional characteristics of the univeristy can promote the establishment of university students. Fourth, the establishment of a research environment and support for start-ups for full-time faculty members can enhance their start-up performance. The university factors that promote the start-up of full-time faculty were research funds and staffes who support start-up. The conclusions drawn from these findings are as follows. First, overall efforts are needed to develop into an entrepreneurial university. Second, in order to change into an entrepreneurial university, direct support for entrepreneurship is needed. Third, as an entrepreneurial university, it is necessary to find a way to bridge the gap by university according to region and size. Fourth, it is necessary to reinforce the support for linking the research results of universities to start-ups. Fifth, it is necessary to improve the atmosphere for full-time faculty members to be entrepreneur.