• 한국도로학회:학술대회논문집
• /
• 2010.09a
• /
• pp.497-502
• /
• 2010

• Communications for Statistical Applications and Methods
• /
• v.21 no.3
• /
• pp.235-243
• /
• 2014

Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.

• Communications for Statistical Applications and Methods
• /
• v.9 no.2
• /
• pp.381-388
• /
• 2002

It has been pointed out that the classical credibility model used in Korea since the beginning of 1990's lacks in objectiveness. Recently, in order to improve objectiveness, the empirical Bayes credibility model utilizing general exposure units like the number of claims and premium has been employed, but that model itself is not quite applicable in the country like Korea whose annual and classified empirical data are not well accumulated and even varied severely. In this article, we propose a new and better model, Based on the new model, we estimate both credibility and loss ratio of each class for fire insurance plans by Korean insurance companies. As a conclusion, we empirically make sure analysis that the number of claims is a more reasonable exposure unit than premium.

• Communications for Statistical Applications and Methods
• /
• v.6 no.2
• /
• pp.501-510
• /
• 1999

In this paper, we consider a comparable study on three Bayes procedures for the multivariate normal mean estimation problem. In specific we consider hierarchical Bayes empirical Bayes and robust Bayes estimators for the normal means. Then three procedures are compared in terms of the four comparison criteria(i.e. Average Relative Bias (ARB) Average Squared Relative Bias (ASRB) Average Absolute Bias(AAB) Average Squared Deviation (ASD) using the real data set.

• Journal of Korean Society of Transportation
• /
• v.27 no.5
• /
• pp.135-144
• /
• 2009

This study estimates the expected number of accidents in Kyungbuk Province to capitalize on experience gained from four years of accident history using the Empirical Bayes (EB) Method. The number of accidents of each site in Kyungbuk Province is recalculated using the Equivalent Property Damage Only (EPDO) method to reflect the severities of the accidents. A cluster analysis is performed to determine similar sites and a unique Safety Performance Function (SPF) is established for each site. The overdispersion parameter is built to correct the difference between the actual number of accidents and the underlying probability distribution. To adjust for varying traffic characteristics of each site, a relative weight is applied and eventually estimates the expected number of accidents. The results show that the highest accident sites are Kimcheon, Youngcheon, and Chilgok, but on the other hand the lowest is Gunwi.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.6
• /
• pp.1241-1247
• /
• 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 applied mathematics & informatics
• /
• v.25 no.1_2
• /
• pp.1-15
• /
• 2007

Consider a Rayleigh distribution with $$pdf\;p(x/{\theta})\;=\;2x{\theta}^{-1}\;{\exp}\;({-x^2}/{\theta})$$ and mean lifetime ${\mu}\;=\;\sqrt{\pi\theta}/2$. We study the two-action problem of testing the hypotheses $H_{0}\;:\;{\mu}{\leq}{\mu}_{0}$ against $H_{1}\;:\;{\mu}\;>\;{\mu}_{0}$ using a linear error loss of ${\mid}{\mu}\;-\;{\mu}_{0}{\mid}$ via the empirical Bayes approach. We construct a monotone empirical Bayes test ${\delta}^{*}_{n}$ and study its associated asymptotic optimality. It is shown that the regret of ${\delta}^{*}_{n}$ converges to zero at a rate $\frac{{\ln}^{2}n}{n}$, where n is the number of past data available when the present testing problem is considered.

• International Journal of Highway Engineering
• /
• v.18 no.4
• /
• 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.

• Journal of the Korean Data and Information Science Society
• /
• v.8 no.1
• /
• pp.41-48
• /
• 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.

• Journal of applied mathematics & informatics
• /
• v.23 no.1_2
• /
• pp.153-165
• /
• 2007

This paper deals with the empirical Bayes two-action problem of testing $H_0\;:\;{\theta}{\leq}{\theta}_0$: versus $H_1\;:\;{\theta}>{\theta}_0$ using a linear error loss for some discrete nonexponential families having probability function either $$f_1(x{\mid}{\theta})=(x{\alpha}+1-{\theta}){\theta}^x\prod\limits_{j=0}^x\;(j{\alpha}+1)$$ or $$f_2(x{\mid}{\theta})=[{\theta}\prod\limits_{j=0}^{x-1}(j{\alpha}+1-{\theta})]/[\prod\limits_{j=0}^x\;(j{\alpha}+1)]$$. Two empirical Bayes tests ${\delta}_n^*\;and\;{\delta}_n^{**}$ are constructed. We have shown that both ${\delta}_n^*\;and\;{\delta}_n^{**}$ are asymptotically optimal, and their regrets converge to zero at an exponential decay rate O(exp(-cn)) for some c>0, where n is the number of historical data available when the present decision problem is considered.