• The Korean Journal of Physiology and Pharmacology
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• v.16 no.2
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• pp.97-106
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• 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.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.119-128
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• 2002

In this paper, we consider the HB estimators of small area means with repeated survey. mao and Yu(1994) considered small area model with repeated survey data and proposed empirical best linear unbiased estimators. We propose a hierachical Bayes version of Rao and Yu by assigning prior distributions for unknown hyperparameters. We illustrate our HB estimator using very popular data in small area problem and then compare the results with the estimator of Census Bureau and other estimators previously proposed.

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

• 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.

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

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

• Journal of Korean Society for Quality Management
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• v.23 no.3
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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.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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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.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.529-544
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• 1996

This paper deals with the problem of estimating the autoregressive random coefficient of a first-order random coefficient autoregressive time series model applied to panel data of time series. The autoregressive random coefficients across individual units are assumed to be a random sample from a truncated normal distribution with the space (-1, 1) for stationarity. The estimates of random coefficients are obtained by an empirical Bayes procedure using the estimates of model parameters. Also, a Monte Carlo study is conducted to support the estimation procedure proposed in this paper. Finally, we apply our results to the economic panel data in Liu and Tiao(1980).

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.83-94
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• 1996

The probability of Yut was calculated by using the physical property in previous study, but this article suggested empirical estimators for probability of Yut. In practice, physics-based probability imposes too strong assumptions, which result in the difference between the calculated probabilies and empirical relative frequencies. Experiment shows the probabilities of Yut depend on the integrated shape of Yut rather than the floor type. Maximum likelihood estimator and empirical Bayes estimators are compared and all turn out to be almost identicla for more than 40 trials. For smaller number of trials, Bayes estimators are recommended for its stability. Regression approach is also adopted as an easy-to-use method without empirical trials.