• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.455-471
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• 2000

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

• 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.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.91-101
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• 2000

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

• 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.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.1-12
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• 2004

In this paper, Yates' end corrections method is centralized to estimate the mean of a population which has a linear trend in the case of k (the reciprocal of the sampling fraction) even. The efficiency of the resultant method is compared with that of existing methods.

• 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.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.457-466
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• 1999

Centered modified systematic sampling (CMSS)' was proposed by Kim(1985) for estimating the mean of a population with a linear trend. In the present paper a version of this sampling method is suggested. This version turns out to be efficient in the same degree as the original method from the viewpoint of the expected mean square error criterion. It is also shown to be quite an efficient method as compared with other existing methods. An illustrative example is given.

• 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.4 no.3
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• pp.743-752
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• 1997

Kim (1985) proposed the so-called "centered balanced systematic sampling" for estimating the mean of a population with a linear trend. In this paper, a version of this sampling method is proposed. It is shown that this version is as efficient as the original method from the viewpoint of the expected mean square error criterion. It is also shown to be quite an efficient method as compared with other existing methods.g methods.