• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.444-460
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• 2017

The duration of volunteering can be analyzed in terms of commitment and attachment. Previous studies have investigated the duration of volunteering predominantly from the perspective of commitment. Alternatively, this study focuses on the concept of attachment and investigates the characteristics of those who volunteer habitually over their whole life, regardless of the regularity and the intensity of the volunteer work. In so doing, the study attempts to identify factors associated with the attachment to volunteering. Data came from a sample of 8,415 participants, ages over twenty who responded to all the surveys of the Korea Welfare Panel Study, from Wave 1 to 10. Zero-inflated negative bionomial regression model was employed to analyze the total number of volunteering in the past ten years. Findings show that people with high attachment to volunteering were those with religion, less education, and a strong sense of reciprocity. Based on the findings, we provide the practical implications for the improved operation and management of volunteer organizations.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.951-961
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• 2011

In this paper, we propose a Bayesian inference using the Markov Chain Monte Carlo(MCMC) method for the zero inflated negative binomial(ZINB) regression model. The proposed model allows the regression model for zero inflation probability as well as the regression model for the mean of the dependent variable. This extends the work of Jang et al. (2010) to the fully defiend ZINB regression model. In addition, we apply the proposed method to a real data example, and compare the efficiency with the zero inflated Poisson model using the DIC. Since the DIC of the ZINB is smaller than that of the ZIP, the ZINB model shows superior performance over the ZIP model in zero inflated count data with overdispersion.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.219-227
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• 2011

In this paper, we proposed a generalized bivariate negative binomial distribution allowing heterogeneous dispersions on two dependent variables based on a trivariate reduction technique. In this model, we propose the score and LR tests for testing the equality of dispersions and compare the efficiencies of the proposed tests using a Monte Carlo study. The Monte Carlo study shows that the proposed score and LR tests prove to be an efficient test for the equality of dispersions in the view of the significance level and power. However, the score test is easier to compute than the LR test and it shows a slightly better performance than the LR test from the Monte Carlo study, we suggest the use of score tests for testing the equality of dispersions on two dependent variables. In addition, an empirical example is provided to illustrate the results.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.413-420
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• 2013

Stochastic weather generator is a commonly used tool to simulate daily weather time series. Recently, a generalized linear model(GLM) has been proposed as a convenient approach to tting these weather generators. In the present paper, a stochastic weather generator is considered to model the time series of daily temperatures for Seoul South Korea. As a covariate, precipitation occurrence is introduced to a relate short-term predictor to short-term predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate a time series of seasonal mean temperatures in the GLM weather generator as a covariate.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.43-49
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• 2010

This study deals with the traffic accident of the Cheongju arterial link sections. The purpose of the study is to develop the traffic accident model. In pursuing the above, this study gives particular attentions to developing the ZAM(zero-altered model) model using the accident data of arterial roads devided by 322 small link sections. The main results analyzed by ZIP(zero inflated Poisson model) and ZINB(zero inflated negative binomial model) which are the methods of ZAM, are as follows. First, the evaluation of various developed models by the Vuong statistic and t statistic for overdispersion parameter ${\alpha}$ shows that ZINB is analyzed to be optimal among Poisson, NB, ZIP(zero-inflated Poisson) and ZINB regression models. Second, ZINB is evaluated to be statistically significant in view of t, ${\rho}$ and ${\rho}^2$ (0.63) values compared to other models. Finally, the accident factors of ZINB models are developed to be the traffic volume(ADT), number of entry/exit and length of median. The traffic volume(ADT) and the number of entry/exit are evaluated to be the '+' factors and the length of median to be '-' factor of the accident.

• 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.

• 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 Korean Society of Transportation
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• v.23 no.1
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• pp.33-44
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• 2005

Railroad crossing crashes are fewer than road crashes, but with regard to crash severity, they can be serious injury crashes. There should be, therefore, enormous efforts to increase the safety of railroad crossings. The objective of this paper is to identify and understand factors associated with railroad crossing crashes. Statistical models are used to examine the relationships between crossing accidents and geometric elements of crossings. The results show the Poisson model is the most appropriate method for the crossing accidents, because overdispersion was not observed. This study identifies seven significant factors associated with railroad crossing crashes through the main and variant models. With regard to explanatory factors on crossing safety, the total traffic volume, daily train volume, presence of commercial area around crossings, distance of train detector from crossings, time duration between the activation of warning signals and gates, crossing types, and speed hump were found to affect the safety of railroad crossings.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.135-144
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• 2009

This study estimates the expected number of accidents in Kyungbuk Province to capitalize on experience gained from four years of accident history using the Empirical Bayes (EB) Method. The number of accidents of each site in Kyungbuk Province is recalculated using the Equivalent Property Damage Only (EPDO) method to reflect the severities of the accidents. A cluster analysis is performed to determine similar sites and a unique Safety Performance Function (SPF) is established for each site. The overdispersion parameter is built to correct the difference between the actual number of accidents and the underlying probability distribution. To adjust for varying traffic characteristics of each site, a relative weight is applied and eventually estimates the expected number of accidents. The results show that the highest accident sites are Kimcheon, Youngcheon, and Chilgok, but on the other hand the lowest is Gunwi.

• 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.