• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.583-592
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• 2015

Zero-inflation has recently attracted much attention in integer-valued time series. This article deals with conditional variance (volatility) modeling for the zero-inflated count time series. We incorporate zero-inflation property into integer-valued GARCH (INGARCH) via conditional Poisson and negative binomial marginals. The Cholera frequency time series is analyzed as a data application. Estimation is carried out using EM-algorithm as suggested by Zhu (2012).

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.67-74
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• 2011

This study deals with the traffic accidents data from the Korean rotaries (circular intersections) to verify their characteristics affected by different vehicle types. This paper categorized the data into three groups based on vehicle types, and developed a set of accident models. The paper proposed two ZIP models and one negative binomial model through a statistical analysis for three vehicle types: automobile, truck and van, and others. The differences among those models were then statistically compared.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.103-110
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• 2011

This study deals with the traffic accidents by type. The objectives are to analyze the characteristics of 2 accident types, and to develop the models by type. In pursuing the above, this paper gives particular attentions to testing the differences between by type two groups, and developing the models (Poisson and negative binomial regressions) using the data of domestic circular intersections. The main results are as follows. First, the number of accidents in vehicle vehicle was analyzed to account for about 73.41% of total and to be higher than vehicle people. Second, two Poisson models and two negative binomial models which were all statistically significant were developed using vehicle people accidents and vehicle vehicle accidents as dependant variables. Finally, the traffic volume as common variable was selected in the models, and right-turn slip lane, speed hump, the number of driveways, the number of pedestrian crossings as specific variables of the models were selected.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Management & Information Systems Review
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• v.33 no.2
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• pp.301-315
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• 2014

The purpose of this study is to estimate the economic value of the Kumjung Mountain, using a Individual Travel Cost Model(ITCM). This paper compares Poisson and negative binomial count data models to measure the tourism demands. Interviewers were instructed to interview only individuals. So the sample was taken in 700. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 60,669 Korean won and the total economic value was estimated to be 252,383 Korean won.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.585-594
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• 2010

This study, investigates the effects of dispersion parameters between two response variables in zero-truncated bivariate generalized Poisson distributions. A Monte Carlo study shows that the zero-truncated bivariate Poisson and negative binomial models fit poorly wherein the zero-truncated bivariate count data has heterogeneous dispersion parameters on dependent variables. In addition, we derive the score test for testing the equality of the dispersion parameters and compare its efficiency with the likelihood ratio test.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.35-46
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• 2008

The purposes of this study are to analyze the characteristics and to develop the models of traffic accidents. In pursuing the above, this study gives particular attentions to developing the models(multiple linear, poisson and negative binomial regression) using the data of Cheongju and Cheongwon signalized intersections. The main results analyzed are as follows. First, the accident characteristics of rural area were defined by factor. Second, 4 accident models which are all statistically significant were developed. Finally, such the variables as $X_2$ and $X_{11}$ were evaluated to be specific variables which reflect the characteristics of rural area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.333-340
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• 2016

The aim of this study is to specifically understand the characteristics of the crime by empirical analysis for the determining factors that affect determining the crime through the space syntax in Busan. In this study, poisson regression and negative binomial regression were used for accurate analysis. 8 variables that were significant of the total 13 variables. The summary if this study based on the results is as follow. Statistically significant variables are female ratio, over 65 population ratio, administration are and commercial area ratio in characteristics. And the more CCTVs a region has, the lower crime rate it shows. As a results of examing whether space syntax variables can predict crime occurrence places. Space with low connectivity come to be a crime causal factor because they have few other related spaces and thereby have low possibility of sudden appearance of interrupters, which results in low surveillance levels of foot passengers. It will provide the basic data that can contribute to urban planning and implementation of crime prevention aspects.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.1-15
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• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.545-567
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• 2018

This study applied and compared Poisson model, negative binomial model, zero inflated Poisson model, and zero inflated negative binomial model to estimate determinants of employed labour quantity. To estimate each of models, this study used fisheries census data which were obtained at microdata integrated service running by Statistics Korea. The study selected zero inflated negative binomial model according to the Vuong test and Likelihood-ratio test. In addition, the study estimated fishing village's practical changes on employed labour quantity as analyzing changes from 2010 to 2015. The results showed that the household with fishing vessels and high selling price had a significant effect on decrease of the labour quantities. Meanwhile, the longer work experience of the household, the more significant the increase in the labour quantities. In conclusion, this study presented that capitalized fishing household and the acceleration of aging had a significant impact on the change in the labour quantities.