• Bulletin of the Korean Mathematical Society
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• v.10 no.2
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• pp.69-75
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• 1973

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.675-694
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• 2008

We propose a new sampling design for the Korean Livestock Production Cost Survey. In this sampling design, the survey population is derived from the 2005’s agricultural census of Korea. And coefficient of variation(CV) is estimated from the current livestock production cost survey data, and the estimated CV’s are used to find the optimal sample size which satisfies the predetermined precision of estimation. In order to save the enumeration cost, the agriculture enumeration districts are used as a primary sampling unit(psu). Final sample is selected by double sampling. Also, we propose the estimator which is able to reflect the change of the population of livestock production households.

• Survey Research
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• v.11 no.1
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• pp.123-144
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• 2010

In new sample design for Korea Housing Survey to research about housing policy, total strata are forty five because individual results of sixteen regions are estimated. The sample size is determined by sample errors of several variables which are the living area, family income, householder income, and living expenses. The sample size of each region is determined by relative standard error of existing result, and the strata sample size is to use the square root proportion allocation. Enumeration districts are sampled by the probability proportion to size systematic sampling in proportion to the enumeration district size, and the systemic sampling to use assortment characteristics. We considered a new apartment complex because of variation reflections which are rebuilder and redevelopment of houses. To get estimators of mean and variance, we used the design weighting, non-response adjusting, and post-stratification. In order to consider estimation efficiency, we calculate the design effect using estimators of variance.

• Journal of Ocean Engineering and Technology
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• v.28 no.3
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• pp.254-259
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• 2014

The infrared signature of a ship is largely influenced by the ocean environment of the operating area, which has been known to cause large changes in the signature. As a result, the weather condition has to be clearly set for an analysis of the infrared signatures. It is necessary to analyze meteorological data for all the oceans where the ship is supposed to be operated. This is impossibly costly and time consuming because of the huge size of the data. Therefore, the creation of a standard environmental variable for an infrared signature research is necessary. In this study, we compared and analyzed sampling methods to represent ocean data close to the Korean peninsula. In order to perform this research, we collected ocean meteorological records from KMA (Korea Meteorological Administration), and sampled these in numerous ways considering five variables that are known to affect the infrared signature. Specifically, a simple random sampling method for all the data and 1-D, 2-D, and 3-D stratified sampling methods were compared and analyzed by considering the mean square errors for each method.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.993-1004
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• 2017

A stratified sampling method is generally used with a sample selected using the same sample weight in each stratum in order to improve the accuracy of the sampling survey estimation. However, the weight should be adjusted to reflect the response rate if the response rate is affected by the value of the variable of interest. It may be also more effective to adjust the weights by subdividing the stratum rather than using the same weight if the variable of interest has a linear relationship with the continuous auxiliary variables. In this study, we propose a method to increase the accuracy of estimation using an informative sampling design technique when the response rate is an exponential function of the variable of interest and the variable of interest has a linear relationship with the auxiliary variable. Simulation results show the superiority of the proposed method.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1047-1061
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• 2015

Stratified random sampling is a powerful sampling strategy to reduce variance of the estimators by incorporating useful auxiliary information to stratify the population. Sample allocation is the one of the important decisions in selecting a stratified random sample. There are two common methods, the proportional allocation and Neyman allocation if we could assume data collection cost for different observation units equal. Theoretically, Neyman allocation considering the size and standard deviation of each stratum, is known to be more effective than proportional allocation which incorporates only stratum size information. However, if the information on the standard deviation is inaccurate, the performance of Neyman allocation is in doubt. It has been pointed out that Neyman allocation is not suitable for multi-purpose sample survey that requires the estimation of several characteristics. In addition to sampling error, non-response error is another factor to evaluate sampling strategy that affects the statistical precision of the estimator. We propose new sample allocation methods using the available information about stratum response rates at the designing stage to improve stratified random sampling. The proposed methods are efficient when response rates differ considerably among strata. In particular, the method using population sizes and response rates improves the Neyman allocation in multi-purpose sample survey.

• Proceedings of the KSCN Conference
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• 2004.05a
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• pp.413.1-413
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• 2004

농촌지역은 건강과 식생활의 자연친화적으로 볼 수 있으나 실제로 농약사용과 과다한 노동 부하와 함께 농업의 세계화 추세에 따라 농업종사자의 정신적 육체적 어려움이 클 것으로 본다. 이에 따라 농촌에서 거주하지만 농업에 종사하는 사람과 비농업에 종사하는 사람들 간에 식품의 생산과 식행동 및 건강관리 행동에 차이를 알아보고 농업종사자의 나은 건강생활을 위한 자료로 활용하기 위하여 본 연구를 실시하였다. 농촌을 행정구역별로 인구비례에 따라 층화추출법으로 1870명을 선발하였다.(중략)

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.321-326
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• 2002

상가건물임대차보호법의 시행령을 제정하는데 필요한 근거정보를 수집하기 위한 임차 사업체조사의 표본설계과정과 추정법을 설명하고 주요 조사결과를 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.141-141
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• 2017

본 연구에서는 대하천의 8개의 수질인자(수온, 용존산소, 수소이온농도, 전기전도도, 총질소, 총인, 탁도, 클로로필-a)를 예측할 수 있는 인공신경망모델을 개발하였다. 인공신경망모델(ANN)은 수질데이터가 가지는 불확실성 및 비정상성, 복잡한 상호관련성에 효과적으로 대응할 수 있는 데이터기반 모델이다. 데이터기반 모델의 특성상 예측정확도를 높이기 위해서 양질의 입력데이터를 구성하는 것이 가장 중요하다. 때문에 각각의 수질인자뿐만 아니라 기상학적 인자 또한 예측을 위한 입력자료로 사용하였으며, 요인분석 및 층화표층추출법을 적용하여 입력데이터를 구성하였고 앙상블기법을 이용하여 추가적으로 예측의 정확도를 향상시켰다. 개발된 모델을 이용하여 지천유입이 있는 북한강의 수질자료를 예측한 결과 탁도를 제외한 7개의 수질인자 모두 0.85 이상의 설명력을 보였으며, 실측값과 예보값을 비교해본 결과 평균적으로 10% 미만의 에러값을 나타냈다. 요인분석을 통하여 연관성있는 인자를 입력인자로 추가한 경우 향상된 결과값을 보였주었으며, 앙상블기법을 적용한 결과 정확도 면에서 큰 향상을 보여주었다.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2895-2905
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• 2018

We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.