• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1033-1041
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• 2013

In this paper, we investigate several variance estimators for pps systematic sampling. Unfortunately, there is no unbiased variance estimators for a systematic sample because systematic sampling can be regarded as a random selection of one cluster. This study provides guidance on which variance estimator may be more appropriate than others in several circumstances. We judge the efficiency of variance estimators for systematic sampling based on of their relative biases and relative mean square error. Also, we investigate variance estimation problems for two-stage systematic sampling applied for the Food Raw Material Consumption Survey and the Establishment Labor Force Survey simulation study, in order to consider the popular two-stage pps systematic sample design for establishment and household survey in Korea.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.26 no.4
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• pp.293-297
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• 1981

An attempt has been made to determine the optimum size of sampling unit and the number of samples for a given precision in wheat, using the data collected from the various experiments in 1979/80. It was found that the coefficients of variation for number of spikes except the case of high-ridge broadcasting by 8HP rotarized seeder are in the same order of those for yield of wheat, and the regression coefficients associated with the coefficients of variation and the size of sampling unit were significant at 1% level of type I error. A wide range of variation in the size of sampling unit was observed for different methods of seeding, indicating the proper sizes of sampling units for 40cm \times 18cm, 60cm \times 18cm, 20cm \times 5cm, 120cm \times 90cm to be 0.40$m^2$, 0.17$m^2$, , 0.11$m^2$, , 0.55$m^2$, , respectively. The variance component for the experimental error was not physically possible to estimate due probably to high variability among the sampling units. The number of the sampling units per plot for a given precision of CV=12% was estimated to be one in an experiment with 4 replicates.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.679-688
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• 2010

Lee (2010) developed a confidence interval for the difference of binomial proportions in two doubly sampled data subject to false-positive errors. The confidence interval seems to be adequate for a general double sampling model subject to false-positive misclassification. However, in many applications, the false-positive error rates could be the same. On this note, the construction of asymptotic confidence interval is considered when the false-positive error rates are common. The coverage behaviors of nine likelihood based confidence intervals are examined. It is shown that the confidence interval based Rao score with the expected information has good performance in terms of coverage probability and expected width.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1080-1083
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• 2000

In this paper, we show that a variation in sampling rate give rise to system performance degradation and propose a method to effectively reduce the error. We first capture the variation as a first order autoregressive (AR) model and project it as an additional sensor measurement noise. By considering that the sensor measurements include correlated noise, we perform a decorrelation process and then apply a standard Kalman filter (SKF) to estimate the target-state. As a result of the two-step procedure, we achieve a significant reduction in the target state estimation error.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.258-260
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• 1995

A novel phase error predictor is proposed for servo system in home-use VCRs. The multirate system in VCRs is converted into a single period sampling system with faster sampling time by using the proposed novel phase error predictor. And the disturbances can be measured much faster. From the experimental results, we can see that the performance of the control system is improved greatly. The phase lock time of the proposed servo system is ten times faster than that of the conventional system.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.100-117
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• 1985

This paper describes an outline of the sampling design for crop area survey and product survey in Korea. The design attempts to from a double statification, to obtain an efficient allocation of the sample and to reduce the sampling error by establishign crop concentrated strata. The optimum numbers of sample field and sample plot are investigated. The design is made it possible to reduce the sampling errors as well as to reduce the sample size further than the present survey.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.411-421
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• 2016

Large frequency limiting distributions of two errors in realized covariance are investigated under noisy and non-synchronous high frequency sampling situations. The first distribution characterizes increased variance of the realized covariance due to noise for large frequency and the second distribution characterizes decreased variance of the realized covariance due to discretization for large frequency. The distribution of the combined error enables us to determine the sampling frequency which depends on a nuisance parameter. A consistent estimator of the nuisance parameter is proposed.

• 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.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.

• 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.