• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.153-162
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• 2008

This study deals with the traffic accidents at the 4-legged signalized intersections in Cheong-ju. The purpose is to comparatively analyze the characteristics and models by the accident type using the data of 143 intersections. In pursuing the above, this study gives particular emphasis to modeling such the accidents as head on collision, rear end collision, side swipe, side right angle collision, and others. The main results are the followings. First, the overdispersion tests show that the negative binomial regression models are appropriate to the traffic accident data in the above contexts. Second, five accident models are developed, which are all analyzed to be statistically significant. Finally, the models are comparatively evaluated using the common variable(ADT) and type-specific variables.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.15-22
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• 2003

In general, the linear regression model has been used to estimate trip generation in the travel demand forecasting procedure. However, the model suffers from several methodological limitations. First, trips as a dependent variable with non-negative integer show discrete distribution but the model assumes that the dependent variable is continuously distributed between -$\infty$ and +$\infty$. Second, the model may produce negative estimates. Third, even if estimated trips are within the valid range, the model offers only forecasted trips without discrete probability distribution of them. To overcome these limitations, a poisson model with a assumption of equidispersion has frequently been used to analyze count data such as trip frequencies. However, if the variance of data is greater than the mean. the poisson model tends to underestimate errors, resulting in unreliable estimates. Using overdispersion test, this study proved that the poisson model is not appropriate and by using Vuong test, zero inflated negative binomial model is optimal. Model reliability was checked by likelihood test and the accuracy of model by Theil inequality coefficient as well. Finally, marginal effect of the change of socio-demographic characteristics of households on trips was analyzed.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.331-347
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• 2014

The purpose of this study is to estimate the economic value of the recreational sea fishing in the Yellow Sea using count data model. For estimating consumer surplus, we used several count data model of travel cost recreation demand such as a poisson model(PM), a negative binomial model(NBM), a truncated poisson model(TPM), and a truncated negative binomial model(TNBM). Model results show that there is no exist the over-dispersion problem and a NBM was statistically more suitable than the other models. All parameters estimated are statistically significant and theoretically valid. The NBM was applied to estimate the travel demand and consumer surplus. The consumer surplus pre trip was estimated to be 254,453won, total consumer surplus per person and per year 1,536,896won.

• 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.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.147-161
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• 1995

The primary objective of this paper is to review parametric models and test statistics related to overdspersion of count data. Poisson or binomial assumption often fails to explain overdispersion. We reviewed real examples of overdispersion in count data that occurred in toxicological or teratological experiments. We also reviewed several models that were suggested for implementing experiments. We also reviewed several models that were suggested for implementing the extra-binomial variation or hyper-Poisson variability, and we noted how these models were generalized and further developed. The approaches that have been suggested for the overdispersion fall into two broad categories. The one is to develop a parametric model for it, and the other is to assume a particular relationship between the variance and the mean of the response variable and to derive a score test staistics for detecting the overdispersion. Recently, Dean(1992) derived a general score test statistics for detecting overdispersion from the exponential family.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.123-135
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• 1999

The rapid increase of Passenger cars which is caused by the discomfort of Public transit and the Preference of automobiles is the major factor of increasing traffic congestions in Seoul With the point that leading the automobilists to the Public transit can be the most important Policy to ease these traffic congestions, this study focuses on the behavioral aspects of company employees and university students and investigates factors influencing bus ridership. To be brief, by estimating bus ridership through count models, this study investigates factors which influence bus ridership and elicits Political suggestions which lead automobilists to Public transit. The Purpose in this study is the application of appropriate count data model. The count data models have been widely applied to the economic area from the middle of the 1980s and to transportation aspect mainly in the foreign countries from the latter half of the 1980s. Even though a few studies in this country employed count data model to count data. all of them were Poisson regression models without suitable tests for the importance of the model specification. In the end, as the result of statistical test, negative binomial regression model which is suitable for overdispersed data was found to be appropriate for the data of weekly bus ridership. To emphasize the importance of model specification, both of poisson regression model and negative binomial regression model were estimated and the results were compared.

• Journal of the Korean Regional Science Association
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• v.31 no.3
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• pp.39-54
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• 2015

To assess an economic value of Cheonggyecheon river restoration project, an in-depth exit survey data was collected to apply travel cost method in this study. Poisson model, Negative Binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial model were executed due to the nature of count data. Empirical results showed that regressors were statistically significant and corresponded to general consumer theory. Since our survey data showed over-dispersion, Zero-truncated Negative Binomial was selected as an optimal one to analyze travel demand of Cheonggyecheon by model goodness of fit test among those aforementioned empirical models. Estimating an economic value of Cheonggyecheon river restoration project, which is known as an ecological river restoration project, we used annual visit of individual traveler and an optimal model. Suffice to say that the annual economic value of Cheonggyecheon river restoration project was estimated as 193.4 billion won in 2013.