• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1241-1247
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• 2012

The paper considers empirical Bayes (EB) and hierarchical Bayes (HB) predictors of the finite population mean under a linear regression model with measurement errors We discuss how to calculate the mean squared prediction errors of the EB predictors using jackknife methods and the posterior standard deviations of the HB predictors based on the Markov Chain Monte Carlo methods. A simulation study is provided to illustrate the results of the preceding sections and compare the performances of the proposed procedures.

• Journal of the Korean Data and Information Science Society
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• 제8권1호
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• pp.41-48
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• 1997

We construct the empirical Bayes(EB) confidence intervals that attain a specified level of EB coverage for the unknown scale parameter in the Weibull distribution with the known shape parameter under the type II censored data. Our general approach is to use an EB bootstrap samples introduced by Larid and Louis(1987). Also, we compare the coverage probability and the expected interval length for these bootstrap intervals with those of the naive intervals through Monte Carlo simulation.

• Communications for Statistical Applications and Methods
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• 제17권6호
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• pp.845-852
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• 2010

The outcomes of counts commonly occur in the area of disease mapping for mortality rates or disease rates. A Poisson distribution is usually assumed as a model of disease rates in conjunction with a gamma prior. The small area typically refers to a small geographical area or demographic group for which very little information is available from the sample surveys. Under this situation the model-based estimation is very popular, in which the auxiliary variables from various administrative sources are used. The empirical Bayes estimator under Poissongamma model has been considered with its accuracy measures. An accuracy measure using a bootstrap samples adjust the underestimation incurred by the posterior variance as an estimator of true mean squared error. We explain the suggested method through a practical dataset of hitters in baseball games. We also perform a Monte Carlo study to compare the accuracy measures of mean squared error.

• 품질경영학회지
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• 제23권3호
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• pp.45-56
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• 1995

The method of lot by lot quality protection for sampling inspection by variables is widely used in quality control. In case of sampling inspection being done repeatedly, one can use the information from the previous sampling inspection to improve current estimates. This article shows that empirical Bayes estimator is superior to the usual sample mean in repeated sampling inspection by variables.

• Interdisciplinary Bio Central
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• 제2권2호
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• pp.4.1-4.6
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• 2010

The most common type of microarray experiment has a simple design using microarray data obtained from two different groups or conditions. A typical method to identify differentially expressed genes (DEGs) between two conditions is the conventional Student's t-test. The t-test is based on the simple estimation of the population variance for a gene using the sample variance of its expression levels. Although empirical Bayes approach improves on the t-statistic by not giving a high rank to genes only because they have a small sample variance, the basic assumption for this is same as the ordinary t-test which is the equality of variances across experimental groups. The t-test and empirical Bayes approach suffer from low statistical power because of the assumption of normal and unimodal distributions for the microarray data analysis. We propose a method to address these problems that is robust to outliers or skewed data, while maintaining the advantages of the classical t-test or modified t-statistics. The resulting data transformation to fit the normality assumption increases the statistical power for identifying DEGs using these statistics.

• 응용통계연구
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• 제9권2호
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• pp.83-94
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• 1996

윷의 확률에 대한 기하학적 접근의 선행연구가 있었고, 이 논문은 그 선행연구를 보완, 발전시키는데 목적을 두고 있다. 특히, 윷의 확률이 '논리적'으로 계산되기 어려운 상황과 그 이유를 설명하고, 통계학적인 추정방법들을 제시하고 있다. 시중에 판매되고 있는 여러가지 종류의 윷을 사용함으로써 실질적인 회귀선을 유도하였고, 이와 같이 추정된 확률을 통하여 도, 개, 걸, 윷, 모의 출현빈도순서 및 예상확률을 구할 수 있게 되었다. 이러한 통계학적인 접근의 결과는 기초확률시간이나 기초통계학 시간에 활용될 수 있을 것이다.

• 한국ITS학회 논문지
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• 제9권2호
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• pp.23-32
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• 2010

도로교통공단은 무인신호위반단속장비의 설치 후 1년 자료를 바탕으로 사고감소효과를 분석하고 있기 때문에, 무인신호위반 설치 후 연도별 사고감소효과에 대한 연구는 부족한 실정이다. 본 연구는 RLC 설치 이후 연도별 3년 동안의 사고 감소효과를 다루고 있다. 연구의 목적은 EB(Empirical Bayes)방법을 이용하여 사고감소 효과를 연도별로 분석하는데 있다. 이를 위해 이 연구는 RLC가 설치된 20개 교차점 951건의 사고자료를 이용한다. 연구의 주요결과는 다음과 같다. 첫째, 포아송 회귀모형을 이용하여 통계적으로 유의한 안전성과함수를 개발하였다. 둘째, EB방법을 이용하여 분석한 결과, 전체적인 사고감소효과는 설치 후 1년 2.73~38.75%, 2년은 6.85~47.36%, 그리고 3년은 6.04~39.31%의 감소효과가 있는 것으로 분석되었다.

• 대한교통학회지
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• 제24권4호
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• pp.31-42
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• 2006

본 연구는 도로안전개선사업의 공간적범위 (지점단위/구간단위)에 따른 도로안전시설물의 효과도 비교를 목적으로 한다. 분석자료는 전라북도 지역 국도를 대상으로 사고잦은지점개선사업과 국도17호선 구간안전개선사업 시행도로에 대한 사전 사후 사고자료와 도로 교통특성자료를 이용하였다 경험적베이즈기법(Empirical Bayes ; EB)을 이용한 시설물별 효과도 산정모형을 구축하고, 비교를 위해서는 승산비 (Odds Ratio)를 이용하여 상대효과도 산정기법을 제시하였다. 분석결과 구간사업에서 설치한 안전시설물이 지점단위 개선사업보다 상대적으로 $7.09%{\sim}77.27%$ 안전성을 개선시키는 것으로 나타났다. 사업의 공간적 범위에 상관없이 구간특성을 가지는 시설물인 중앙분리대와 가드레일은 상대효과도가 크지 않게 나타났으나, 대표적인 지점설치 시설물인 갈매기표지나 미끄럼방지포장 등은 구간사업에서 그 상대효과도가 매우 크게 나타나 향후 시설물 설치시 구간측면에서 고려가 필요함을 알 수 있었다. 이와 같은 연구결과를 토대로 보았을 때 향후 안전시설물 설치와 같은 도로안전개선사업은 구간단위 사업이 확대되어야 할 것으로 보인다.

• Journal of the Korean Statistical Society
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• 제32권2호
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• pp.121-150
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• 2003

The National Health Interview Survey (NHIS) is one of the surveys used to assess the health status of the US population. One indicator of the nation's health is the total number of doctor visits made by the household members in the past year, There is a substantial nonresponse among the sampled households, and the main issue we address here is that the nonrespones mechanism should not be ignored because respondents and nonrespondents differ. It is standard practice to summarize the number of doctor visits by the binary variable of no doctor visit versus at least one doctor visit by a household for each of the fifty states and the District of Columbia. We consider a nonignorable nonresponse model that expresses uncertainty about ignorability through the ratio of odds of a household doctor visit among respondents to the odds of doctor visit among all households. This is a hierarchical model in which a nonignorable nonresponse model is centered on an ignorable nonresponse model. Another feature of this model is that it permits us to "borrow strength" across states as in small area estimation; this helps because some of the parameters are weakly identified. However, for simplicity we assume that the hyperparameters are fixed but unknown, and these hyperparameters are estimated by the EM algorithm; thereby making our method Bayes empirical Bayes. Our main result is that for some of the states the nonresponse mechanism can be considered non-ignorable, and that 95% credible intervals of the probability of a household doctor visit and the probability that a household responds shed important light on the NHIS.

• 한국도로학회논문집
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• 제15권4호
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• pp.135-146
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• 2013

PURPOSES : This study aimed to analyze the impact the operation of pre-signals at 4-leg signalized intersections and present primary environmental factors of roads that need to be considered in the installation of pre-signals. METHODS : Shift of proportions safety effectiveness evaluation method which assesses shifts in proportions of target collision types to determine safety effectiveness was applied to analyze traffic crash by types. Also, Empirical Bayes before/after safety effectiveness evaluation method was adapted to analyze the impact pre-signal installation. Negative binomial regression was conducted to determine SPF(safety performance function). RESULTS : Pre-signals are effective in reducing the number of head on, right angle and sideswipe collisions and both the total number of personal injury crashes and severe crashes. Also, it is deemed that each factor used as an independent variable for the SPF model has strong correlation with the total number of personal injury crashes and severe crashes, and impacts general traffic crashes as a whole. CONCLUSIONS: This study suggests the following should be considered in pre-signal installation on intersections. 1) U-turns allowed in the front and rear 2) A high number of roads that connect to the intersection 3) Many right-turn traffic flows 4) Crosswalks installed in the front and rear 5) Insufficient left-turn lanes compared to left-turn traffic flows or no left-turn-only lane.