• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.795-805
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• 1997

In this paper, we consider a Bayesian forecasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under dynamic generalized linear models. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.91-102
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• 1999

A new method is developed for estimating the mean of a population which has a linear trend. The suggested estimator is based on the balanced systematic sampling method and the concept of interpolation and extrapolation. The efficiency of the proposed method is compared with that of conventional methods.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.17-24
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• 2001

A method is proposed for efficiently estimating the mean of a population which has a linear trend. The proposed estimator is based on the centered modified systematic sampling method and the concept or interpolation. Using the expected mean square error criterion, it is shown that the proposed method is more efficient than conventional methods in most real cases.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1103-1118
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• 2009

When we wish to estimate the mean or total of a finite population, the numbering of the population units is of importance. In this paper, we have proposed two methods for estimating the mean or total of a population having a linear trend, for the case when the reciprocal of the sampling fraction is an even number and the sample size is an odd number. The first method involves drawing a sample by using a method which is a generalization of Singh et al's (1968) modified systematic sampling, and using interpolation in determining the estimator. The second method involves selecting a sample by modified systematic sampling, and estimating the population parameters by the regression estimation method. Under the criterion of the expected mean square error based on Cochran's (1946) infinite superpopulation model, the proposed methods have been compared with existing methods. We have also made a comparison between the two proposed methods.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.457-476
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• 2000

In this study, we have proposed a sampling method and an estimation method for efficiently estimating the mean of a population which has a linear trend. These methods involve drawing a sample by the so-called "centered balanced systematic sampling", which is an extension of systematic sampling, and then estimating the population mean with an adjusted estimator, not with the sample mean itself. We used the concept of interpolation in determining the adjusted estimator.\Ve compared the efficiency of the proposed estimator with those of the estimators from existing methods, under the expected mean square error criterion based on the infinite superpopulation model introduced by Cochran(1946). The proposed method is for use in the case when the sample size n(2 5) is an odd number and k(the reciprocal of the sampling fraction) is an even number. A good result was also obtained in an example using computer simulation. simulation.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.261-274
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• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.153-161
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• 2009

We consider a logistic model with random effects as the superpopulation for estimating the small area pro-portions. The best linear unbiased predictor under linear mired model is popular in small area estimation. We use this type of estimator under logistic mixed motel for the small area proportions, on which the estimation of mean squared error is also discussed. Two kinds of estimation methods, the parametric bootstrap and the linear approximation will be compared through a Monte Carlo study in the respects of the normality assumption on the random effects distribution and also the magnitude of sample sizes on the approximation.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.329-340
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• 1999

We consider a Bayesian forcasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under multiprocess dynamic generalized linear models. The multiprocess dynamic model offers a powerful framework for the modelling and analysis of time series which are subject to a abrupt changes in pattern. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

• Genomics & Informatics
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• v.12 no.1
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• pp.42-47
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• 2014

Asian populations contain a variety of ethnic groups that have ethnically specific genetic differences. Ethnic variants may be highly relevant in disease and human differentiation studies. Here, we identified ethnically specific variants and then investigated their distribution across Asian ethnic groups. We obtained 58,960 Pan-Asian single nucleotide polymorphisms of 1,953 individuals from 72 ethnic groups of 11 Asian countries. We selected 9,306 ethnic variant single nucleotide polymorphisms (ESNPs) and 5,167 ethnic variant copy number polymorphisms (ECNPs) using the nearest shrunken centroid method. We analyzed ESNPs and ECNPs in 3 hierarchical levels: superpopulation, subpopulation, and ethnic population. We also identified ESNP- and ECNP-related genes and their features. This study represents the first attempt to identify Asian ESNP and ECNP markers, which can be used to identify genetic differences and predict disease susceptibility and drug effectiveness in Asian ethnic populations.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.105-117
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• 2004

In this paper, a new method is developed for estimating the mean of a population which has a linear trend. This method involves drawing a sample by the modified systematic sampling, and then estimating the population mean with an adjusted estimator, not with the sample mean itself. We use the method of least squares in determining the adjusted estimator. The proposed method is shown to be more and more efficient as the linear trend becomes stronger. It turns out to be relatively efficient as compared with the conventional methods if $\sigma$$^2$the variance of the random error term in the infinite superpopulation model, is not very large.