• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.172-172
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• 2016

지난 2008년부터 2013년까지 우리나라는 홍수방어 및 가뭄을 대비하기 위하여 하천정비사업인 4대강 사업을 실시하였다. 또한, 4대강 사업은 환경적인 측면을 고려하기 위해 하천변에 대체습지를 조성하였다. 하지만, 대체습지 조성 이후 대체습지에 대한 평가가 제대로 이루어지지 않아 관리하는데 있어 문제가 발생하고 있다. 따라서 대체습지에 대해 기능을 평가하고 평가 결과를 통해 관리방안을 수립하는 것이 필요하다. 현재 습지의 기능은 수문학적, 생태학적, 지형학적으로 구분하여 평가하고 있다. 본 연구에서는 대체습지의 수문학적 평가를 위해 필요한 대체습지 제원 및 수리수문요소 등 관련자료를 수집하였다. 빈도해석과 수문모형을 통해 침수빈도, 침수심 등을 분석하여 수문학적 측면으로 대체습지를 평가하였다. 본 연구의 결과는 4대강 사업으로 조성된 대체습지의 관리방안을 수립하는데 기초자료로 활용될 것으로 기대된다.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.1-14
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• 2000

We consider statistical methods for nonresponse problem in social and economic sample surveys. To create a complete data set, which does not include item nonresponse data, imputation methods are generally used. In this paper, we introduce some imputation methods and compare them with one another. Also, we consider some problems, which occur when an imputed data set is treated as a response data set. Due to the imputed values, the true variance of the estimator after imputation is increased by the imputation variance. However, since usual naive variance estimator constructed from the imputed data set does not estimate the imputation variance, the true variance of the estimator after imputation tends to be underestimated. Theoretical reason is investigated and serious results are explained through a simulation study. Finally, some adjusted variance estimation methods to compensate for underestimation are presented and discussed.

• Survey Research
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• v.1 no.2
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• pp.1-14
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• 2000

We consider statistical methods for nonresponse problem in social and economic sample surveys. To create a complete data set, which does not include item nonresponse data, imputation methods are generally used. In this paper, we introduce some imputation methods and compare them with one another. Also, we consider some problems, which occur when an imputed data set is treated as a response data set. Due to the imputed values, the true variance of the estimator after imputation is increased by the imputation variance. However, since usual naive variance estimator constructed from the imputed data set does not estimate the imputation variance, the true variance of the estimator after imputation tends to be underestimated. Theoretical reason is investigated and serious results are explained through a simulation study. Finally, some adjusted variance estimation methods to compensate for underestimation are presented and discussed.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.377-390
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• 2017

When conducting a survey, item nonresponse occurs if the respondent does not respond to some items. Since analysis based only on completely observed data may cause biased results, imputation is often conducted to analyze data in its complete form. The panel study is a survey method that examines changes of responses over time. In panel studies, there has been a preference for using information from response values of previous waves when the imputation of item nonresponses is performed; however, limited research has been conducted to support this preference. Therefore, this study compares the performance of imputation methods according to whether or not information from previous waves is utilized in the panel study. Among imputation methods that utilize information from previous responses, we consider ratio imputation, imputation based on the linear mixed model, and imputation based on the Bayesian linear mixed model approach. We compare the results from these methods against the results of methods that do not use information from previous responses, such as mean imputation and hot deck imputation. Simulation results show that imputation based on the Bayesian linear mixed model performs best and yields small biases and high coverage rates of the 95% confidence interval even at higher nonresponse rates.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.49-54
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• 2004

본 연구에서는 표본 농가의 교체나 무응답으로 인한 데이터의 손실을 최소화하기 위하여 핫덱방법을 적용할 때 필요한 무응답 대체군 형성 방안을 제안하였다. 농가경제조사의 무응답 현황과 특성을 살펴보고, 대체군 형성 방안들을 비교할 수 있는 측도를 제안하였다. 제안된 비교 측도를 이용해서 대체군 형성 방안들을 비교하였다.

• Korean Journal of Environmental Biology
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• v.35 no.1
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• pp.21-36
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• 2017

Phthalates, known as typical endocrine disruptors, are plasticizers used to soften plastics such as polyvinyl chloride (PVC). Because of their material properties, phthalates are used extensively in the production of toys, flooring, wood processing, detergents, and even cosmetics as lubricants and perfume solvents. Due to their endocrine disrupting effect and other adverse health effects published, recently, phthalates have been regulated in many countries. Besides, in an effort to replace phthalates, several chemical plasticizers such as trioctyltrimellitate (TOTM) and dioctylterephthalate (DIOP) have been used instead of the existing harmful phthalates, and novel alternatives are continuously being developed. Nonetheless, phthalates are still being detected in several plastic products, and the safety of alternatives that are considered safe is being questioned. In this review, we describe the adverse health effects of phthalates, their regulation and the current status of their alternatives.

• Applied Biological Chemistry
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• v.33 no.1
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• pp.43-51
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• 1990

Meat emulsions containing 0, 15, 30 and 45% of soy protein isolate(SPI), Na-caseinate(Na-CN) and their mixtures were prepared in order to determine the effect of these non-meat proteins on the physical properties and their sensory quality in emulsion type sausage. It was found that SPI was better fat stabilizer and better binder than Na-CN. The mixtures of SPI and Na-CN didn't exert any significant effect on emulsion stability. From the texture profile analysis by using Instron two-cycle compression tests, decrease in the substitution levels and increase in the ratio of SPI/Na-CN resulted in a significant increase in the textural values of hardness, adhesiveness, gumminess, chewiness. The finished products showed that the substituted product for 15 % meat protein had higher textural values than the unsubstituted product. The sensory quality evaluated for the final products showed no significant difference between the SPI substituted product for 15 % meat protein and the unsubstituted product. However, all of the substituted products for 15 % meat protein and some of those for 30 % substitution with SPI and 67 % SPI received higher scores than average.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.407-426
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• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.899-907
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• 2010

Several non-response imputation methods are suggested, however, mainly cross-sectional imputations are studied and applied to this analysis. A simple and common imputation method for panel data is the cross-wave regression imputation or carry-over imputation as a special case of cross-wave regression imputation. This study suggests a multiple imputation method combined time series analysis and cross-sectional multiple imputation method. We compare this method and the cross-wave regression imputation method using MSE, MAE, and Bias. The 2008 monthly labor survey data is used for this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.291-291
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• 2021

모형이 갖는 불확실성의 정량화나 매개변수의 최적화는 계산시간의 기하급수적인 증가를 가져온다. 계산시간의 효율성을 극대화할 수 있는 기법으로 최근 대체모형이 개발되었으며, 다양한 분야에서 적용되고 있다. 그러나 대체모형은 훈련된 데이터 공간에서 크게 벗어난 극한 사상를 정확하게 모의하기는 어려운 단점이 있다. 본 연구는 이와 같은 대체모형의 단점을 개선할 수 있는 새로운 PCK(polynomial chaos-krigging) 기법을 제시한다. PCK는 PCE(polynomial chaos expansion) 기법과 OK(ordinary krigging) 기법을 결합한 것이며, PCK의 효과는 기존의 PCE 및 OK 모형의 결과와 비교하여 입증하였다. 본 연구의 분석 결과는 다음과 같다. (1) PCK는 더 적은 수의 훈련 샘플만으로도 원래 모형을 더 정확하게 대체할 수 있다. (2) 원래 훈련 샘플보다 약 3배 더 큰 극한사상을 모의했을 때, PCE와 OK는 예측이 실패하였지만, PCK의 예측은 정확하였다. (3) 민감도 분석 결과 PCK의 매개변수 특성과 거동이 PCE 및 OK보다 원래 모형의 특성과 거동에 더 일치한다. 본 연구에서는 3개의 대체모형의 결과를 원래모형의 결과와 비교하였으며 그 적용성을 극한강우에 대해 검토하였다. 일반적으로 훈련 샘플의 범위와 비슷한 강우사상에 대해서는 모든 대체모형의 결과가 우수하였으나, 훈련 샘플의 범위에서 벗어난 극한 사상의 모의는 PCK만 적용이 가능하였다. 제안된 대체모형은 극한사상의 예측에 있어 기존 대체모형보다 매우 향상된 정확도를 제공함을 확인할 수 있었다.