• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.133-141
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• 2009

This study was conducted to support for determining an efficient sampling design for forest resources assessments in South Korea with respect to statistical efficiency. For this objective, different systematic sampling designs were simulated and compared based on an artificial forest population that had been built from field sample data and satellite data in Yang-Pyeong County, Korea. Using the k-NN technique, two thematic maps (growing stock and forest cover type per pixel unit) across the test area were generated; field data (n=191) and Landsat ETM+ were used as source data. Four sampling designs (systematic sampling, systematic sampling for post-stratification, systematic cluster sampling, and stratified systematic sampling) were employed as optimum sampling design candidates. In order to compute error variance, the Monte Carlo simulation was used (k=1,000). Then, sampling error and relative efficiency were compared. When the objective of an inventory was to obtain estimations for the entire population, systematic cluster sampling was superior to the other sampling designs. If its objective is to obtain estimations for each sub-population, post-stratification gave a better estimation. In order to successfully perform this procedure, it requires clear definitions of strata of interest per field observation unit for efficient stratification.

• Survey Research
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• v.10 no.1
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• pp.155-168
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• 2009

As an efficient sampling design, stratified random sampling is often used when auxiliary information is available at the designing stage. Although one - per - stratum design is an efficient design that can be used when many auxiliary variables are available, it does not provide any unbiased variance estimator. With a two - per - stratum sample in which two elements are selected from each stratum, it is possible to obtain an unbiased variance estimator. However the loss of efficiency could be significant if any important stratification variable is missed. In this study, we investigated a sampling design that uses the all given auxiliary information and also permits an unbiased variance estimator suggested by Park and Fuller(2008). Through a simulation study, we compared several stratified random sampling and systematic sampling design. We also applied the proposed stratified sampling designs to 2007 youth panel data.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.370-377
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• 2006

This study was conducted to develop an efficient method of sampling design appropriate for the sustainable forest management. For this, data were collected in Yangpyung-Gun, Gyunggi Province based on three different sampling designs such as systematic design, systematic cluster design, and stratified cluster design. Based on evaluation statistics, the sampling designs were compared to select a sampling method fitted to sustainable forest management. It was found that the systematical cluster sampling is the most efficient sampling method in terms of feasibility for sustainable forest management. It was also recommended that the sample plots should be made as a cluster of triangle-shape. The clusters should be consisted of a main plot and three sub-plots. And the sub-plots should be arranged with a distance of 50m from the main plot in the center of cluster.

• Survey Research
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• v.6 no.2
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• pp.1-32
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• 2005

The accuracy of exit poll mainly depends on the sampling method of voting places. For exit poll, we propose a probability sampling method of selecting voting places as an alternative to the bellwether polling place sampling. Through an empirical study based on the 2004 general election data, the efficiency of the suggested systematic sampling from ordered voting places was evaluated in terms of mean prediction error and it turns out that the proposed sampling method outperformed the bellwether polling places sampling. We also calculated the variance of estimator from the proposed sampling, and considered the sample size problem to guarantee the target precision using the design effect of the proposed sample design.

• 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.

• 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.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1193-1196
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• 2003

This paper proposes a 2x oversampling method with a smart sampling for a clock and data recovery(CDR) circuit in a 2.5Gbps serial data link. In the conventional 2x oversampling method, the "bang-bang" operation of the phase detection produces a systematic jitter in CDR. The smart sampling in phase detection helps the CDR to remove the "bang-bang" operation and to improve the jitter performance. The CDR with the proposed 2x oversampling method is designed using Samsung 0.25${\mu}{\textrm}{m}$ process parameters and verified by simulation. Simulation result shows the proposed 2x oversampling method removes the systematic jitter.e systematic jitter.

• Journal of Nutrition and Health
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• v.17 no.3
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• pp.236-241
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• 1984

In order to make clear the relationship between sample design and sample survey in community, it was conducted research on sample design for National Nutrition Survey in 1983. In this paper it was tried to analize the data based on The Report of a Settled Population, 1981 conducted by National Bureau of Statistics Economic Planning Board. The sample was basically using stratified two-stage sampling with systematic sampling of Ban or Li as administrative unit. The population represents the whole nation excluding Jeju-do because of budget. The selection of sampling unit and sampling procedure was as follows. 1) Stratify the nation-wide area in 20 sections according to administrative districts. 2) Determine the sample size in each section according to equal proportional rate (1 / 8040) and to about 1,000 households in the sample. 3) Select the 25 sampling units by section according to households proportion. 4) Select the 10 households at random from each Ban or Li according to equal probability proportion as the final sampling unit. Using the procedure, it was sampled 1,000 households for National Nutrition Survey in 1983.