Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김성욱 | - |
dc.date.accessioned | 2023-07-24T01:35:06Z | - |
dc.date.available | 2023-07-24T01:35:06Z | - |
dc.date.issued | 2012-07 | - |
dc.identifier.citation | 한국데이터정보과학회지, v. 23, NO. 4, Page. 851-858 | - |
dc.identifier.issn | 1598-9402 | - |
dc.identifier.uri | http://koreascience.or.kr/article/JAKO201225067514697.page | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/184248 | - |
dc.description.abstract | We consider a bivariate Poisson regression model to analyze discrete count data when two dependent variables are present. We estimate the regression coefficients associated with several safety countermeasures. We use Markov chain and Monte Carlo techniques to execute some computations. A simulation and real data analysis are performed to demonstrate model fitting performances of the proposed model. | - |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2011-0028933). | - |
dc.language | en | - |
dc.publisher | 한국데이터정보과학회 | - |
dc.subject | Accident prediction model | - |
dc.subject | bivariate Poisson distribution | - |
dc.subject | Gibbs sampler | - |
dc.subject | Metropolis-Hastings algorithm | - |
dc.subject | safety countermeasure | - |
dc.title | Bayesian analysis for the bivariate Poisson regression model: Applications to road safety countermeasures | - |
dc.type | Article | - |
dc.relation.no | 4 | - |
dc.relation.volume | 23 | - |
dc.identifier.doi | 10.7465/jkdi.2012.23.4.851 | - |
dc.relation.page | 851-858 | - |
dc.relation.journal | 한국데이터정보과학회지 | - |
dc.contributor.googleauthor | 최형구 | - |
dc.contributor.googleauthor | 임준범 | - |
dc.contributor.googleauthor | 원용호 | - |
dc.contributor.googleauthor | 이수범 | - |
dc.contributor.googleauthor | 김성욱 | - |
dc.sector.campus | E | - |
dc.sector.daehak | 과학기술융합대학 | - |
dc.sector.department | 수리데이터사이언스학과 | - |
dc.identifier.pid | seong | - |
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