• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.431-443
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• 2004

For the purpose of disease mapping, we consider the four small area estimation techniques to estimate the mortality rate of small areas; direct, Empirical estimation with total moment estimator and local moment estimator, Estimation based on hierarchial generalized linear model. The estimators are compared by empirical study based on lung cancer mortality data from 2000 Annual Reports on the Cause of Death Statistics in Gyeongsang-Do and Jeonla-Do published by Korean National Statistical Office. Also he stability and efficiency of these estimators are investigated in terms of mean square deviation as well as variation of estimates.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.443-461
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• 2009

In order to overcome the lack of Korean credit rating migration data, we consider an empirical Bayes procedure to estimate credit rating migration matrices. We derive the posterior probabilities of Korean credit rating transitions by utilizing the Moody's rating migration data and the credit rating assignments from Korean rating agency as prior information and likelihood, respectively. Metrics based upon the average transition probability are developed to characterize the migration matrices and compare our Bayesian migration matrices with some given matrices. Time series data for the metrics show that our Bayesian matrices are stable, while the matrices based on Korean data have large variation in time. The bootstrap tests demonstrate that the results from the three estimation methods are significantly different and the Bayesian matrices are more affected by Korean data than the Moody's data. Finally, Monte Carlo simulations for computing the values of a portfolio and its credit VaRs are performed to compare these migration matrices.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.453-459
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• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.21-30
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• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level, and based on the time the performances of items are investigated at the normal stress level. In this paper, when the mean of the prior of a failure rate is known in the exponential lifetime distribution with censored accelerated failure time data, we utilize the empirical Bayesian method by using the moment estimators in order to estimate the parameters of the prior distribution and obtain the empirical Bayesian predictive density and predictive intervals for a future observation under the normal stress level.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.103-111
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• 2011

To evaluate highway safety countermeasures or identify high risk sites, the expected crashes for a site (or segment) have been estimated using the panel crash data. Past studies show that two different methods can be employed to estimate the expected crashes: observed crash based method and empirical Bayes (EB) method. This study conducts a simulation study to analyze how the estimation errors of the two estimates are affected by the different structures of the panel crash data and the presence of the change in safety over time. The results disclose that the estimation errors of the observed crash based estimates (i.e. the mean observed crash and comparative parallel estimate) are always greater than those of the EB estimates regardless of the structure of the panel crash data and the presence of the change in safety over time. Thus, it is highly recommended that the EB method be used in the study of traffic safety to obtain more reliable estimates for the expected crashes. In addition, this study corroborates that the estimation errors of the two estimates decrease as the analysis periods increase if safety does not change over time. Hence, it is also recommended that the 1-year analysis period used for identifying high risk sites in Korea be extended to produce more efficient estimates of the time-constant expected crashes.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.113-124
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• 2006

Among tile traffic safety facilities, median barriers are installed above 4-lane national roads due to the awareness of haying an effect on preventing the front collision. Studies about the installation effect analysis of median harrier have been carried out through both at home and outside, mainly indicating total accident reduction effect on pertinent sections. In sum, study about how the accident occurrence form is changed at the point classified by the accident type or severity is insignificant. In the case of outside the country, calculating the accident reduction effect according to the type of median barriers is main research and in domestic, though there is a part of researches assessing reduction effect by accident types, it is not reliable in the view or statistics because of using only 1year's before-aftev data installing the facility, So in this Paper. it is the main purpose to presume the accident conversion effect. For this, we conduct an investigation and collect data about 7-year's accident data containing before-after Project, safety facilities foundation records and index of road alignment on the subject of 4-1ane national roads(108.6km) existing median barrier. Next. using the empirical bayes method, we estimate a model construction and accident conversion effect of accident type severity. We expect the result or this Paper will be applied for a policy execution and Presentation of facility standard related to median barrier from now on.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.1-29
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• 2007

Suppose one is trying to estimate a high dimensional vector of parameters from a series of one observation per parameter. Often, it is possible to take advantage of sparsity in the parameters by thresholding the data in an appropriate way. A marginal maximum likelihood approach, within a suitable Bayesian structure, has excellent properties. For very sparse signals, the procedure chooses a large threshold and takes advantage of the sparsity, while for signals where there are many non-zero values, the method does not perform excessive smoothing. The scope of the method is reviewed and demonstrated, and various theoretical, practical and computational issues are discussed, in particularly exploring the wide potential and applicability of the general approach, and the way it can be used within more complex thresholding problems such as curve estimation using wavelets.

• Journal of Preventive Medicine and Public Health
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• v.40 no.3
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• pp.233-238
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• 2007

Objectives : We aimed to assess the relationship between long-term exposure to air pollution and lung cancer in the Republic of Korea. Methods : Using the Annual Report of Ambient Air Quality in Korea, Annual Report of National Cancer Registration, and Annual Report on the Cause of Death Statistics, we calculated the standardized mortality ratio (SMR) and standardized incidence ratio (SIR) of lung cancer for both sexes in 74 areas from 7 Korean metropolitan cities. We performed random intercept, Poisson regression using empirical Bayes method. Results : Both SMRs and SIRs in the 7 metropolitan cities were higher in women than in men. Mean SIRs were 99.0 for males and 107.0 for females. The association between $PM_{10}$ and lung cancer risk differed according to gender. $PM_{10}$ was not associated with the risk of lung cancer in males, but both incidence and mortality of lung cancer were positively associated with $PM_{10}$ in females. The estimated percentage increases in the rate of female lung cancer mortality and incidence were 27% and 65% at the highest $PM_{10}$ category $({\geq}70\;{\mu}g/m^3)$, compared to the referent category $({\geq}50\;{\mu}g/m^3)$. Conclusions : Long-term exposure to $PM_{10}$ was significantly associated with female lung cancer incidence in 7 Korean metropolitan cities. Further study is undergoing to estimate the relative risk of $PM_{10}$ using multi-level analysis for controlling individual and regional confounders such as smoking and socioeconomic position.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.689-699
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• 2013

This paper studies the partial credibility application method by assuming the empirical prior or noninformative prior informations in auto insurnace business where intensive rating segmentation is expanded because of premium competition. Expanding of rating factor segmetation brings the increase of pricing cells, as a result, the number of cells for partial credibility application will increase correspondingly. This study is trying to suggest more accurate estimation method by considering the Bayesian framework. By using empirically well-known or noninformative information, inducing the proper posterior distribution and applying the Bayes estimate which is minimizing the error loss into the credibility method, we will show the advantage of Bayesian inference by comparison with current approaches. The comparison is implemented with square root rule which is a widely accepted method in insurance business. The convergence level towarding to the true risk will be compared among various approaches. This study introduces the alternative way of redcuing the error to the auto insurance business fields in need of various methods because of more segmentations.