• Communications for Statistical Applications and Methods
• /
• 제3권3호
• /
• pp.215-223
• /
• 1996

By using Tukey's generalized lambda distribution, appoximate posterior density is derived under the Bayes-empirical Bayes model. The sensitivity of posterior distribution to the hyperprior distribution is examined by using Tukey's generalized lambda distriburion which approximate many well-knmown distributions. Based upon Monte Varlo simulation studies it can be said that posterior distribution is sensitive to the cariance of the prior distribution and to the symmetry of the hyperprior distribution. Also posterior distribution is approximately obtained by using the following methods : Lindley method, Laplace method and Gibbs sampler method.

• 대한교통학회:학술대회논문집
• /
• 대한교통학회 2007년도 제57회 학술발표회논문집
• /
• pp.412-417
• /
• 2007

• 한국도로학회:학술대회논문집
• /
• 한국도로학회 2010년 추계학술대회 논문집
• /
• pp.497-502
• /
• 2010

• Journal of the Korean Data and Information Science Society
• /
• 제24권4호
• /
• pp.885-893
• /
• 2013

This paper considers Bayes estimations of the small area means under Fay-Herriot model with measurement errors. We provide empirical Bayes predictors of small area means with the corresponding jackknifed mean squared prediction errors. Also we obtain hierarchical Bayes predictors and the corresponding posterior standard deviations using Gibbs sampling. Numerical studies are provided to illustrate our methods and compare their eciencies.

• 대한교통학회지
• /
• 제27권5호
• /
• pp.135-144
• /
• 2009

본 연구는 경북도내에서 발생한 4년간의 교통사고 자료를 대상으로 Empirical Bayes (EB) 방법을 이용하여 예상사고건수를 예측하였다. 경북도내 각 군과 시 지역의 교통사고는 대물피해환산법을 적용하여 심각도를 반영하였으며, EB 방법을 적용하기 위해 군집분석을 통해 유사한 지역을 선정하였고, 선정된 유사지역을 대상으로각 지역별 안전성능함수(SPF)를 도출하였다. 실제 사고건수와의 근원적인 확률분포를 일치시키기 위해 과분산 파라메타를 산출하였으며, 지역별 교통특성을 반영하기 위해 가중치를 적용하여 예상 사고건수를 예측하였다. 분석 결과 김천시, 영천시, 칠곡군 순으로 가장 높은 사고건수가 예상되는 반면, 군위군이 가장 낮은 사고건수가 발생할 것으로 예측되었다.

• The Korean Journal of Physiology and Pharmacology
• /
• 제16권2호
• /
• pp.97-106
• /
• 2012

The pharmacokinetics/pharmacodynamics analysis software NONMEM$^{(R)}$ output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM$^{(R)}$ VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.

• 한국도로학회논문집
• /
• 제18권4호
• /
• pp.93-102
• /
• 2016

PURPOSES : There are many recently constructed roundabouts in Jeollabuk-do province. This study analyzed how roundabouts reduce the risk of accidents and improve safety in the province. METHODS : This study analyzed safety improvement at roundabouts by using an accident prediction model that uses an Empirical Bayes method based on negative binomial distribution. RESULTS : The results of our analysis model showed that the total number of accidents decreased from 130 to 51. Roundabouts also decreased casualties; the number of casualties decreased from 7 to 0 and the seriously wounded from 87 to 16. The effectiveness of accident reduction as analyzed by the accident prediction model with the Empirical Bayes method was 60%. CONCLUSIONS : The construction of roundabouts can bring about a reduction in the number of accidents and casualties, and make intersections safer.

• 한국도로학회논문집
• /
• 제17권1호
• /
• pp.119-127
• /
• 2015

PURPOSES : Before-and-after studies of red light cameras were conducted with the aim of reducing the number of side right-angle collisions. Three different methods were used for the before-and-after studies, and the analysis results were compared. METHODS : This research used the naive before-and-after method, the comparison-group method, and the empirical Bayes method to study the effects of red light cameras on side-angle collisions. The results of the three before-and-after methods were compared and interpreted in terms of safety indications at signalized intersections. RESULTS : The research results showed that side right-angle collisions can be reduced by installing red light cameras at signalized intersections. All three methods guarantee safety improvements of 25~30% on average. With regard to the results of each method, the naive before-and-after method, the comparison-group method, and the empirical Bayes method showed safety improvements of 25.6%, 27.8%, and 29.7%, respectively. CONCLUSIONS : It was concluded that red light cameras are an effective countermeasure to improve intersection safety. In particular, by installing red light cameras, side right-angle collisions can be reduced by up to approximately 25~30%.

• 한국ITS학회 논문지
• /
• 제8권6호
• /
• pp.46-54
• /
• 2009

본 연구는 무인신호위반단속장비의 사고감소 효과를 다루고 있다. 연구의 목적은 EB (Empirical Bayes)방법을 이용하여 사고감소 효과를 분석하는데 있다. 이를 위해 무인신호위반단속장비가 설치된 28개 교차점 728건의 사고자료를 이용한다. 연구의 주요결과는 다음과 같다. 첫째, 단순사고건수 방법의 사고감소 효과는 20.74%로 분석되었다. 둘째, 포아송과 음 이항 회귀모형을 이용하여 SPF모형이 개발되었으며, 과분산계수가 0에 가까워 포아송 회귀모형이 음이항 회귀모형보다 더 적합한 것으로 평가되었다. 아울러 포아송 모형의 ${\rho}^2$값이 0.409로 나타나 통계적으로 유의한 모형으로 분석되었다. 마지막으로, EB방법을 이용한 분석 결과, 사고가 3.89%에서 29.23% 감소된 것으로 나타났다.

• 품질경영학회지
• /
• 제42권4호
• /
• pp.747-756
• /
• 2014

Purpose: The purpose of this study is to apply the Bayesian estimation methodology for producing 'Korean Standard -Quality Excellence Index' model and prove the effectiveness of the new approach based on survey data by comparing the current index with the new index produced by Bayesian estimation method. Methods: The 'Korean Standard -Quality Excellence Index' was produced through the collected survey data by Bayesian estimation method and comparing the deviation with two results for confirming the effectiveness of suggested application. Results: The statistical analysis result shows that suggested estimator, that is, empirical Bayes estimator improves the effectiveness of the index with regard to reduce the error under specific loss function, which is suggested for checking the goodness of fit. Conclusion: Considering the Bayesian techniques such as empirical Bayes estimator for producing the quality excellence index reduces the error for estimating the parameter of interest and furthermore various Bayesian perspective approaches seems to be meaningful for producing the corresponding index.