• Journal of Korean Society of Transportation
• /
• v.23 no.4 s.82
• /
• pp.47-55
• /
• 2005

In recent years, the rapid growth of vehicles have increased traffic crashes. Since they can cause the economic losses and have put the life qualify in danger, there should be numerous efforts to reduce traffic crashes. To reduce traffic crashes, this research seeks to improve the safety of intersections by analysing causations of injury severity with Ordered Probability Model. This research applied the Ordered Probit Model, which assumes that ${\epsilon}_i$(random error) is normally distributed, for model calibration and used $p^2$ (likelihood ratio) and $x^2$ (Chi-square) for model selection. The results show that minor road traffic, heavy vehicle rates, major and minor right-turn rates, presence of lightings, speed limits, instructive line for left-turn traffic are significant factors affecting crash severities at signalized intersections.

• The Korean Journal of Applied Statistics
• /
• v.33 no.1
• /
• pp.25-46
• /
• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.348-348
• /
• 2021

가뭄 연구의 궁극적 목표는 가뭄 발생의 메커니즘에 대한 이해를 높이고, 예측기술을 향상시켜 선제적 대응이 가능하도록 하는 것이다. 일반적으로 가뭄분석에 활용되는 가뭄지표는 연속형 변수로 간주하여 확률모형을 구축하지만, 가뭄상태와 가뭄피해 자료는 순서형 및 이산형 변수이므로 범주형 자료 분석 기법을 적용하는 것이 더 적절하다. 따라서 본 연구에서는 기상학적 가뭄과 피해발생 사이의 관계를 규명하기 위해 범주형 자료 분석 방법 중 로그선형(log-linear) 모형과 로지스틱(logistic) 회귀모형을 활용하였다. 가뭄피해 예측을 위한 가뭄 피해 정보를 수집하는 것은 매우 어려운 일이다. 가뭄의 영향으로 인해 발생할 수 있는 피해의 종류가 다양하며, 여러 분야의 이해관계자가 받아들이는 가뭄의 피해 양상이 다르기 때문이다. 본 연구에서는 국가가뭄정보포털(drought.go.kr)에서 충청북도의 가뭄피해현황 자료를 수집하였다. 30년(1991~2020년)동안 238개 읍면동 중 34개 행정구역에서 총 272건의 가뭄피해가 발생한 것으로 확인되었다. 표준강수지수(SPI)를 이용하여 분석된 지역별 연평균 가뭄발생횟수는 약 8.44회이며, 가뭄이 가장 많이 발생한 해는 2001년(평균 가뭄발생 18.7회)이었다. 강수의 부족으로 인해 발생하는 기상학적 가뭄이 사회경제적 피해를 야기하는 수문학적 가뭄으로 전이되기까지 몇 주에서 몇 달까지 시간이 소요된다. 이러한 관계를 파악하기 위해 가뭄피해 발생 여부를 예측변수, 가뭄피해 발생 이전의 가뭄상태를 설명변수로 설정하여 기상학적 가뭄 발생에 따른 가뭄피해 발생 확률을 산정하였다. 그 결과 가뭄피해 발생 당시의 가뭄상태보다 그 이전에 연속된 가뭄상태가 있을 경우 가뭄피해 발생 확률이 약 2.5배 상승하는 것으로 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.2
• /
• pp.437-444
• /
• 2017

The purpose of this study is to analyze the factors affecting the reverse mortgage utilization and satisfaction of the elderly. Based on the survey data of the reverse mortgage demand in 2016, we carried out empirical analysis using the binary logit model and the ordered logit model. First of all, as a result of the empirical analysis using the binary logit model, the determinants of using the reverse mortgage were age, region, assets, household member, children with financial help, and education level. As a result of the empirical analysis using the ordered logit model, the determinants of the satisfaction level of the reverse mortgage were estimated to be age, gender, and region. Based on the results of the empirical analysis, it is necessary to find a way to increase the participation rate of the reverse mortgage and to improve the satisfaction of the user.

• Journal of Environmental Impact Assessment
• /
• v.25 no.2
• /
• pp.124-140
• /
• 2016

Using the Korea Labor Institute Panel Study(KLIPS), this study investigates the impacts of water pollution on life satisfaction in Korea. Panel random-effects ordered probit model is used to consider the ordered property of life satisfaction data and heterogeneity of panel data. The proxy variables to reflect the degree of water pollution are biochemical oxygen demand(BOD) and total phosphorus(TP). In addition to the environmental variables above, other determinants used in various studies on life satisfaction such as economic, social, and demographic characteristics are included. Estimation results show that water pollution is negative and significant for life satisfaction. Other indicators such as income, age, house ownership, gender, education are positively related while urban residence and own business are shown to be negatively related.

• Journal of the Korean Regional Science Association
• /
• v.35 no.2
• /
• pp.59-71
• /
• 2019

Korea's average annual working hours are among the highest in the OECD. Such long-term work has been a factor that reduces the quality of life by discouraging workers' productivity and interrupting the compatibility of work and family, prompting the government to encourage flexible work systems, such as increasing part-time jobs, but a lack of quality part-time jobs. Part-time work enables flexible labor for workers, but at the same time, workers will involuntarily opt for part-time work as they have poor working conditions and negative social views. In this respect, the effect of the working type on an individual's life is expected to be different. In addition, for women, gender gaps exist in the labor market and the impact of part-time work on life satisfaction is expected to differ from men in terms of working and family alike. Using the data from the 2017 "Seoul Survey Urban Policy Indicator Survey", the ordered logistic regression model was used to analyze the cross-effect of working type and sex on satisfaction. The analysis of the study showed that when other factors were controlled, life satisfaction was high in the order of fulltime female, full-time male, part-time female, and part-time male. In addition, further analysis shows that the parttime female workers have the highest probability of choosing low life satisfaction, while the probability of choosing high life satisfaction is the lowest, and full-time male workers have the lowest probability of choosing low life satisfaction, while the highest probability of choosing high life satisfaction is the highest.

• The Korean Journal of Applied Statistics
• /
• v.24 no.5
• /
• pp.915-930
• /
• 2011

There are a variety of methods to model game results and many methods exist for the case of paired comparison data. Among them, the Bradley-Terry model is the most widely used to derive a latent preference scale from paired comparison data. It has been applied in a variety of fields in psychology and related disciplines. We applied this model to the data of Korean Baseball League. It shows that the loglinear Bradley-Terry model of defensive rate and save is optimal in terms of AIC. Also some categorical characteristics, such as east team and west team, existence of golden glove winning players, team(s) with seasonal pitching leader, and team(s) with home advantage, influenced the game result significantly. As a result, the suggested models can be further utilized to predict future game results.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.6D
• /
• pp.791-799
• /
• 2008

To build the system which has high utilization and usefulness for users, it is necessary to know the information type and use-demand that the use want. The purpose of this study is to forecast the preference and demand of utilization for bus information when bus information is offered through cellular phon. The accomplishments of this research are as follow : Firstly, importance on the level of individual factor and the value of change's figure can be evaluated, using preference analysis on bus information by conjoint analysis. Secondly, by establishing the use-demand model bus information using binary logit model, influence factor on whether or not the use of the user. Finally, ordered probit model was built by use behavior model in payment per call or per month of potential user of bus information. Through call times and sensitive analysis by payment methods, elasticity point, optimal payment fee, and use probability was analyzed. This study make application as basic to efficient bus information policy and to improve use rate of bus information in future because this study make it possible to get preference analysis, use-demand analysis and estimation of optimal payment fee which is reflecting various requirement in use of bus information user.

• Journal of Korean Society of Rural Planning
• /
• v.16 no.1
• /
• pp.1-8
• /
• 2010

The purpose of this paper is to estimate a probability to visit the Yeosu Aquarium with an ordered logit model. Ordered logit model is affordable to estimate the probability when the dependant variable represents likert-type scale. The estimated results are as follows. The more income induces the visiting-expectation. The experience for another aquarium and the visiting-expectation for the Yeosu EXPO are contributed to the visiting-expectation for the Yeosu Aquarium. The needs to visit the Yeosu Aquarium is low in Kyoungsang area and Seoul-Kyounggi-Incheun Metropolitan area. This is related to the Aquarium facilities, which were established in each area. In average level conditions regarding to all independent variables the probability to visit the Yeosu Aquarium is calculated to 15.75%. However, the probability to visit to the Yeosu Aquarium is decreasing according to the change of an admission fee.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2060-2071
• /
• 1999

The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.