• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.15 no.6
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• pp.883-897
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• 2008

This paper provides correct informations inflecting the present situation using the sample design in population that the National Statistical Office puts in operation of the mining and manufacturing industry statistical survey in 2006. This paper proposes new sampling design which is able to grasp business fluctuations and provide basic data for the rearing policy and management of the material industry and components industry. These sample design are the modified cut-off method and multivariate Neyman allocation using principal components and sampling method is the probability proportional systematic sampling.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.187-193
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• 1996

This paper presents a new approach to modify the traditional method for sampling inspectionby variables to suit undesired measurement conditions. On the basis of a systematic analysis of the effects of measurement errors on different types of acceptance schemes this paper gives two modified equations for revising the sampling size η and the acceptability constant $textsc{k}$ to form a new acceptance scheme (η'$textsc{k}$) under undesired measurement conditions. It has proved that the new method is suitable to different types of sampling inspection by variables including that for mean value and that for percent defective. The new acceptance scheme based on the proposed technique provides an engineering feasibility to replace the traditional scheme to suit undesired measurement conditions.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.393-402
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• 2004

We suggest a summary of sample design for the statistical survey of E-commerce to estimate the general trend as well as the market size and investment scale of e-commerce based on the Census on Basic Characteristic of Establishments(CBCE). The sample design of this survey is composed of systematic sampling and modified cut-off method.