• Journal of the Korean Data and Information Science Society
• /
• v.9 no.2
• /
• pp.247-253
• /
• 1998

In ease of the epidemic Zero-Inflated Poisson model, likelihood ratio test was used for testing epidemic alternatives. Epidemic changepoints were estimated by the method of least squares. It were used for starting points to estimate the maximum likelihood estimators. And several parameters were compared through the Monte Carlo simulations. As a result, maximum likelihood estimators for the epidemic chaagepoints and several parameters are better than the least squares and moment estimators.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.2
• /
• pp.177-186
• /
• 2003

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correlated response variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.

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

• International Journal of Highway Engineering
• /
• v.11 no.2
• /
• pp.151-158
• /
• 2009

This study deals with the rear-end collisions in the rural aiea. The objectives of this study are 1) to analyze the characteristics of rear-end accidents of signalized intersections, and 2) to develop the accident models for Cheongju-Cheongwon. In pursing the above, this study gives the particular attentions to comparing the characters of urban and rural area. In this study, the dependent variables are the number of accidents and value of EPDO(equivalent property damage only), and independent variables are the traffic volumes and geometric elements. The main results analyzed are the followings. First, the statistical analyses show that the Poisson accident model using the number of accident as a dependant variable are statistically significant and the negative binomial accident model using the value of EPDO are statistically significant. Second, the independent variables of Poisson model are analyzed to be the ratio of high-occupancy vehicles, total traffic volume and the sum of exit/entry, and those of negative binomial regression are the main road width, total traffic volume and the ratio of high-occupancy vehicles. Finally, the specific independent variables to the rural area are the main road width, the ratio of high occupancy vehicle, and the sum exit/entry.

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

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.155-165
• /
• 1995

반복측정자료의 분석을 위해 제안된 Liang and Zeger(1986)의 회귀모형은 일반화추정식(generalized estimationg equations, GEE)을 이용하여 모형의 모수를 추정한다. 이 모형은 반복측정된 반응변수와 설명변수들과의 관계를 추정하는 것이 주된 목적이기 때문에 회귀모수는 중요한 모수로 간주되나 산포모수는 중요하지 않은 장애모수(nuisance parameters)로 간주된다. 일반적으로 GEE 분석에서 회귀모수의 추정량은 산포모수에 상관없이 일치적(consistent)으로 얻어진다고 알려져 있다. 그러나 본 논문에서는 포아송분포를 따르는 반복측정자료에 대한 사례연구와 모의 실험을 통해서 일반적으로 믿어져왔던 것과는 달리 GEE 방법이 산포모수에 민감하게 영향을 받고 있음을 보였다. 특히 산포모수의 값이 일정하지 않은 경우에는 GEE 방법이 산포모수에 민감 하게 영향을 받고 있음을 보였다. 특히 산포모수의 값이 일정하지 않은 경우에는 GEE 방법에서 밝혀진 회귀모수 추정량의 일치성에도 문제가 발생할 수 있음을 보였다.

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

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.6
• /
• pp.46-54
• /
• 2009

This study deals with the effects on the accident reduction according to the installation of RLC (red light cameras). The objective is to analyze the effects on the accident reduction using EB (Empirical Bayes) method. In pursuing the above, the study uses the 728 accident data occurred at the 28 intersections which RLC are installed. The main results are as follows. First, the effects of accident reduction were analyzed to be 20.74% by simple before-after study method. Second, the safety performance functions (SPF) were developed by the Poisson and negative binominal regression models, and since the over-dispersion parameter was close to zero, Poisson model was evaluated to be more appropriate than the negative binominal model. Also, the Poisson model was analyzed to be statistically significant because its ${\rho}^2$ value was 0.409. Finally, the results of analysis using an EB method showed that the accidents were reduced by range from 3.89 to 29.23%.

• Journal of Korea Water Resources Association
• /
• v.37 no.10
• /
• pp.813-822
• /
• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• The Korean Journal of Applied Statistics
• /
• v.16 no.2
• /
• pp.335-349
• /
• 2003

In this paper, we use Bayesian method for model selection of poisson vs. negative binomial distribution, and normal, double exponential vs. cauchy distribution. The fractional Bayes factor of O'Hagan (1995) was applied to Bayesian model selection under the assumption of noninformative improper priors for all parameters in the models. Through the analyses of real data and simulation data, we examine the usefulness of the fractional Bayes factor in comparison with intrinsic Bayes factors of Berger and Pericchi (1996, 1998).