• Title/Summary/Keyword: Infinite superpopulation model

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An Estimator of Population Mean Based on Balanced Systematic Sampling When Both the Sample Size and the Reciprocal of the Sampling Fraction are Odd Numbers

  • Kim, Hyuk-Joo
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.667-677
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    • 2007
  • In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

On the Effectiveness of Centering, Interpolation and Extrapolation in Estimating the Mean of a Population with Linear Trend

  • Kim, Hyuk-Joo;Jung, Sun-Ju
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.365-379
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    • 2002
  • We apply the techniques of interpolation and extrapolation to derive a new estimator based on centered modified systematic sampling for the mean of a population which has a linear trend. The efficiency of the proposed estimation method is compared with that of various existing methods. An illustrative numerical example is given.

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Efficient Estimation of Population Mean Using Centered Modified Systematic Sampling and Interpolation

  • Kim, Hyuk-Joo;Choi, Byoung-Chul
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.175-185
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    • 2002
  • 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 of 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.

A Study on Estimating Population Mean by Use of Interpolation and Extrapolation with Balanced Systematic Sampling

  • Kim, Hyuk-Joo
    • 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.

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Estimation of Population Mean Using Centered Modified Systematic Sampling and Interpolation

  • Kim, Hyuk-Joo;Choi, Byoung-Chul
    • 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.

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Generalization of modified systematic sampling and regression estimation for population with a linear trend (선형추세를 갖는 모집단에 대한 변형계통표집의 일반화와 회귀추정법)

  • Kim, Hyuk-Joo;Kim, Jeong-Hyeon
    • 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.

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Efficient Estimation of the Mean for Populations with a Linear Trend : An Extension of Systematic Sampling (선형추세를 갖는 모집단에 대한 효율적인 모평균 추정 : 계통추출의 확장)

  • 김혁주;석은양
    • 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.

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Estimation of Population Mean Using Modified Systematic Sampling and Least Squares Method (변형된 계통추출과 최소제곱법을 이용한 모평균 추정)

  • 김혁주
    • 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.