• Title/Summary/Keyword: 무한초모집단 모형

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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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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.