• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.179-186
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• 2017

Technology forecasting is predict future trend and state of technology by analyzing the results so far of developing technology. In general, a patent has novel information about the result of developed technology, because the exclusive right of technology included in patent is protected for a time period by patent law. So many studies on the technology forecasting using patent data analysis has been performed. The patent keyword data widely used in patent analysis consist of occurred frequency of the keyword. In most previous researches, the continuous data analyses such as regression or Box-Jenkins Models were applied to the patent keyword data. But, we have to apply the analytical methods of discrete data for patent keyword analysis because the keyword data is discrete. To solve this problem, we propose a patent analysis methodology using Bayesian Poisson discrete model. To verify the performance of our research, we carry out a case study by analyzing the patent documents applied by Apple until now.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.475-484
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• 2018

Gamma generalized linear models are useful for non-negative and skewed responses. However, these models have received less attention than Poisson and binomial generalized linear models. In particular, hypothesis testing for the significance of regression coefficients has not been thoroughly studied. In this paper we assess the performance of various test statistics for gamma generalized linear models based on numerical studies. Our results show that the likelihood ratio test and F-type test are generally recommended and that the partial deviance test should be avoided in practice.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.485-494
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• 2011

When the observations can take only the non-negative integer values, it is called the count data such as the numbers of car accidents, earthquakes, or insurance coverage. In general, the Poisson regression model has been used to model these count data; however, this model has a weakness in that it is restricted by the equality of the mean and the variance. On the other hand, the count data often tend to be too dispersed to allow the use of the Poisson model in practice because the variance of data is significantly larger than its mean due to heterogeneity within groups. When overdispersion is not taken into account, it is expected that the resulting parameter estimates or standard errors will be inefficient. Since coverage is the main issue for insurance, some accidents may not be covered by insurance, and the number covered by insurance may be zero. This paper considers the zero-inflated model for the count data including many zeros. The performance of this model has been investigated by using of real data with overdispersion and many zeros. The results indicate that the Zero-Inflated Negative Binomial Regression Model performs the best for model evaluation.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.47-56
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• 2008

Generally, accident exposure at intersections is relatively higher than that at roadway segments due to more possibility of merging, diverging, turning, crossing, and weaving maneuver. Furthermore, the traffic accident rate at intersections has been rapidly increasing since 1990's. Since there is more opportunity of conflict at unsignalized intersection, frequency and severity of traffic accident are more severe than signalized intersections. The purpose of the study is to analyze factors causing vehicle crashes and provide intersection design guidelines to improve intersection safety. For this study, vehicle to vehicle crash data of 116 rural 3 legs unsignalized were collected and field surveys were conducted for traffic and geometric conditions. Ordered probit models were developed to analyze the severity of crashes. It was found that weather, obstacles in minor roadsides, presence of major exclusive right lane, presence of major road crosswalk, difference between posted speed of major road and minor road, land-use around intersections, shoulder width of major road, ADT of major road are significant factors for intersection safety.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.33-40
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• 2009

This study deals with the traffic accidents of elderly drivers. The objectives are to comparatively analyze the characteristics of accident between the elderly and other drivers, and to develop the models of traffic accidents. In pursuing the above, this paper gives particular attentions to testing the differences between the above two groups, and developing the models(Poisson and negative binomial regression) using the data of Cheongju 4-legged signalized intersections. The main results analyzed are as follows. First, the differences between the elderly and other drivers' accidents were clearly defined by the time of day, accident type, etc. Second, 3 accident models which were all statistically significant were developed. Finally, the differences between elderly and other drivers' models were comparatively analyzed using the common and specific variables.

• 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.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.145-155
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• 2012

At present, Seoul City is putting the bus exclusive lane system into practice according to mass transit revitalization policy. Starting with the installation of roadside bus exclusive lane in the past, at present, even the road sections for central- lane bus exclusive lane system are on the increase. The purpose of this research is to analyze the factors giving impacts on bus accident on central bus exclusive lane and roadside bus exclusive lane. In case of the central bus exclusive lane, the 6 variables, such as the number of bus routes, number of access & entrance to central lanes patterns, whether the stop line of central lanes retreats or not, separated distance between the stop line of central lanes and crosswalks, traffic volume, and number of bus routes stopping at bus stops on reversible lanes, were found to have a significant influence on bus accidents. In case of roadside bus exclusive lane sections, the four variables such as the number of right-turn bus routes, whether to be chronic illegal parking & stopping, time for the walk signal, and forms of land use, etc. were found to have a significant influence on bus accident.

• Journal of Korean Society of Transportation
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• v.31 no.2
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• pp.20-32
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• 2013

This study is aimed at identifying the relationship of transit accessibility types to its related travel frequency in the Seoul metropolitan area. A multi-level poisson regression model is employed after categorizing transit accessibility into 18 types based on locations of residential and work workplace. Analysis results offer three policy implications in improving transit use in the Seoul metropolitan area. First, increase in transit ridership can be more effectively attained when policies concerning both competitive and complementary relationships between bus and rail transit are incorporated. Second, transfer system needs to be focused on such two modal perspectives as one travels from Seoul to suburban area and residential areas given the fact that walking accessibility to bus transit is good but that to rail transit is poor. Third, it is more effective to emphasize rail transit priority rather than bus transit, especially for the travel from suburban area to the city of Seoul in order to increase transit ridership.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.361-368
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• 2013

This research aims to offer the information required for demand increase on marketing strategy level by investigating Mudeungsan visitors' demographic characteristics and social economical variables. To accomplish this study, the proper analyzing model needs to be applied because a grave error of parameters will be led if regression model appropriate for analyzing the data of a continuous probability variable is applied, in case that dependent variable is a discrete random variable which have a discrete probability distribution. Therefore data analysis was performed with Poisson model. However, as the data was showing an overdispersion, parameter was estimated with the Binomial Poisson model able to cover the problem. As a result, some explanatory variables turned out to be significant such as visitor's age, occupation, preferred season to visit, type of company, five days working, and preferring type of tourism. Author could offer to the national park the information about characteristics of core market revealed and marketing strategy for it, based on those influential variables.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2941-2951
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• 2018

The purpose of this paper is to analyse the effect of ocean weather factors on shipments of swimming crab. We use the data of data portal and ocean weather factors (mean wind velocity, mean atmospheric pressure, mean relative humidity, mean air temperature, mean water temperature, mean maximum wave height, mean significant wave height, maximum significant wave height, maximum wave height, mean wave period, maximum wave period). We did statistical analysis using Poisson regression analysis and negative binomial regression analysis. As the result of study, important factors influential in the shipments of swimming crab turn out to be mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature, maximum wave height, mean wave period and maximum wave period. the shipments of swimming crab increases as mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature increases or mean wave period increase. However, as maximum wave height, maximum wave period decreases, the shipment of swimming crab increases.