• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.1-10
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• 2004

In the Korean Economically Active Population Survey(EAPS), the sample sizes for small areas are typically too small to provide reliable estimators because the EAPS has been designed to produce unemployment statistics for large areas such as Metropolitan Cities and Province. In this study, we consider the synthetic and composite estimators for the unemployment rate of small areas, and apply them to real data on Choongbook province which is from the Korean EAPS of December 2000. The mean square errors of these estimators were estimated by the Jackknife method, and the efficiencies of small area estimators were evaluated in terms of the relative standard errors and the relative root mean square errors. As a result, the composite estimator is much more efficient than other estimators and it turns out that the composite estimator can produce the reliable estimates of the unemployment rate of small areas under the current EAPS system.

• 대한인간공학회지
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• 제22권4호
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• pp.59-78
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• 2003

Most regression models of anthropometric variables use stature and/or weight as regressors; however, these 'flat' regression models result in large errors for anthropometric variables having low correlations with the regressors. To develop more accurate regression models for anthropometric variables, this study proposed a method to estimate anthropometric variables in a hierarchical manner based on the relationships among the variables and a process to develop and improve corresponding regression models. By applying the proposed approach, a hierarchical estimation structure was constructed for 59 anthropometric variables selected for the occupant package design of a passenger car and corresponding regression models were developed with the 1988 US Army anthropometric survey data. The hierarchical regression models were compared with the corresponding flat regression models in terms of accuracy. As results, the standard errors of the hierarchical regression models decreased by 28% (4.3mm) on average compared with those of the flat models.

• 한국도로학회논문집
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• 제16권3호
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• pp.119-129
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• 2014

PURPOSES : This investigational survey is to observe a proper spatial aggregation method for path travel time estimation using the hi-pass DSRC system. METHODS : The links which connect the nodes of section detectors location are used for path travel time estimation traditionally. It makes some problem such as increasing accumulation errors and processing times. In this background, the new links composition methods for spatial aggregation are considered by using some types of nodes as IC, JC, RSE combination. Path travel times estimated by new aggregation methods are compared with PBM travel times by MAE, MAPE and statistical hypothesis tests. RESULTS : The results of minimum sample size and missing rate for 5 minutes aggregation interval are satisfied except for JC link path travel time in Seoul TG~Kuemho JC. Thus, it was additionally observed for minimum sample size satisfaction. In 15, 30 minutes and 1 hour aggregation intervals, all conditions are satisfied by the minimum sample size criteria. For accuracy test and statistical hypothesis test, it has been proved that RSE, Conzone, IC, JC links have equivalent errors and statistical characteristics. CONCLUSIONS : There are some errors between the PBM and the LBM methods that come from dropping vehicles by rest areas. Consequently, this survey result means each of links compositions are available for the estimation of path travel time when PBM vehicles are missed.

• 한국ITS학회 논문지
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• 제13권6호
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• pp.64-76
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• 2014

본 연구는 자동차주행거리 추정과정에서 발생할 수 있는 오차발생 원인을 규명하였다. 그리고 각 원인이 자동차주행거리 추정 정확도에 미치는 영향을 오차율로 정량화하여 효율적인 자동차주행거리 추정방안을 제시하였다. 이를 위한 연구과정은 다음과 같다. 첫째, 시범조사 지역을 대상으로 자동차주행거리 추정 방법론의 정확도를 검증하기 위한 자동차주행거리 관측 자료를 구축하였다. 둘째, 자동차주행거리 추정 오차발생 원인은 표본크기, 표본추출방법, 단위구간 설정방법의 오류로 구분하였다. 그리고 각 원인에 따른 자동차주행거리 추정오차를 최소화하기 위한 다양한 방법론을 설정하였다. 셋째, 각 방법론에 의한 자동차주행거리 추정 오차율을 비교분석 하였다. 마지막으로 Toy-Network를 구축하여 지역특성을 고려한 자동차주행거리 추정방안을 제시하였다. 본 연구는 실험 계획적 접근방법을 통하여 효율적인 자동차주행거리 추정방안을 제시하였으며, 추정 정확도 검증을 위하여 자동차주행거리 관측 자료를 활용했다는 점에서 의의를 갖는다. 또한 본 연구에서 제시한 자료수준과 지역특성을 고려한 자동차주행거리 추정 방안은 향후 지역별 자동차주행거리 추정에 기여할 것으로 판단된다.

• Communications for Statistical Applications and Methods
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• 제17권3호
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• pp.337-347
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• 2010

대부분의 통계조사는 전국 및 시도단위와 같은 전체 또는 규모가 큰 지역을 위한 통계작성이 가능하도록 설계되어 있다. 그러나 최근들어 소규모 지역의 신뢰있는 통계결과에 대한 통계 이용자들의 요구가 점점 증가하고 있다. 경제활동인구조사는 전국 및 16개 시도를 위한 실업률을 매월 작성하고 있으나, 시군별 직접추정량은 적은 표본규모 때문에 신뢰도가 낮다. 본 연구에서는 경제활동인구조사에서 제공되는 실업자수에 대한 통계를 시군별로 작성하기 위한 모형을 제시한다. 이를 위해 보조정보로부터 "정보를 빌려오는(borrow strength)" 지역단위모형(Area level model)을 사용하였다. 제안된 모형 기반 추정(Model-based Estimation)은 모형 오차의 정규성 가정을 기반으로 하고 있으며, 평균제곱오차 측면에서 제안된 모형들을 비교하였다.

• Journal of the Korean Data and Information Science Society
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• 제26권3호
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.337-344
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• 1998

통계청에서 조사 발표한 '96가구소비실태조사의 지역결과 자료에 대한 통계적 신뢰도를 분석하며, 전국 혹은 넓은 지역을 대상으로 하는 조사에서 소지역 통계의 오차를 줄여 신뢰도를 높이는 추정방법을 제안한다.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.739-751
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• 2001

In this paper, a sample design is studied for 2000 forestry management survey of five types forestry , tree felling, gathering of pine mushroom, growing of nut trees, growing of wild flowers, and lumbering industry. We introduce population stratification and a modified stratified cut-off sampling which deal with determination of sample size, sample allocation, and estimation of total and variance of estimator. Substitution of sample units and imputation of nonresponse units are discussed for reducing the nonsampling errors.

• 한국지하수토양환경학회지:지하수토양환경
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• 제17권6호
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

• 경영과학
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• 제30권2호
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.