• 품질경영학회지
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• 제19권2호
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• pp.86-95
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• 1991

Empirical Bayes estimation of the binomial parameter ${\theta}$ is considered when the sample size in each component problem is random. The result is applied to the lot acceptance sampling problem in the presence of various kinds of costs including cost for sampling.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2002년도 춘계학술대회 발표논문집
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• pp.74-84
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• 2002

본 연구에서는 1970년 Royall에 의해 표본추출방법의 한 대안으로서 다시 주목받기 시작한 균형추출방법(purposive selection or balanced sampling)과 확률추출방법(random sampling)의 장.단점을 층화추출법과 비추정량의 경우를 예로 들어 비교하고자 한다. 균형추출방법은 강건성(robustness)과 효율성(efficiency) 측면에서 확률추출방법은 추출의 간편성과 사회적 인식 측면에서 각각의 장점을 지니고 있는 것으로 볼 수 있다.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.471-479
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• 2007

This paper discusses about how to build up mixed-effects model for analysing ordinal response data by using cumulative logits. Random factors are assumed to be coming from the designed sampling scheme for choosing observational units. Since the observed responses of individuals are ordinal, a proportional odds model with two random effects is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

• Journal of the Korean Statistical Society
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• 제31권1호
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• pp.93-107
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• 2002

Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

• 한국지하수토양환경학회지:지하수토양환경
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• 제21권6호
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• pp.179-191
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• 2016

In addition to the measurement of the concentration of soil contaminants, the new idea of indicative parameters was proposed to validate the remedial works through the monitoring for the changes of soil characteristics after applying the clean up technologies. The parameters like CFU (colony forming unit), pH and soil texture were recommended as indicative parameters for land farming. In case of soil washing, water content and the particle size distribution of the sludge were recommended as indicative parameters. The sludge is produced through the particle separation process in soil washing and it is usually treated as a waste. The parameters like water content, organic matter content, CEC (cation exchange capacity) and CFU were recommended as indicative parameters for the low temperature thermal desorption method. Besides the indicative parameter, sampling methods in stock pile and the optimal minimum amount of composite soil sample were proposed. The rates of sampling error in regular grid, zigzag, four bearing, random grid methods were 17.3%, 17.6%, 17.2% and 16.5% respectively. The random grid method showed the minimum sampling error among the 4 kinds of sampling methods although the differences in sampling errors were very little. Therefore the random grid method was recommended as an appropriate sampling method in stock pile. It was not possible to propose a value of optimal minimum amount of composite soil sample based on the real analytical data due to the dynamic variation of $CV_{fund{\cdot}error}$. Instead of this, 355 g of soil was recommended for the optimal minimum amount of composite soil sample under the assumption of ISO 10381-8.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권3호
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• pp.208-216
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• 2009

유전자알고리즘의 교차나 돌연변이 연산을 직접적으로 사용하지 않고 개체군의 확률분포를 추정하여 보다 효율적인 탐색을 수행하려는 분포추정알고리즘이 여러 방법으로 제안되었다. 그러나 실제로 변수들간의 고차상관관계를 파악하는 일은 쉽지 않은 일이라 대부분의 경우 낮은 차수의 상관관계를 제한된 가정하에 추정하게 된다. 본 논문에서는 데이타의 고차상관관계를 표현할 수 있고 최적 해를 좀 더 효율적으로 찾을 수 있는 새로운 분포추정알고리즘을 제안한다. 제안된 알고리즘에서는 상관관계가 있을 것으로 추정되는 변수들의 집합으로 정의된 하이퍼에지로 구성된 랜덤 하이퍼그래프 모델을 구축하여 변수들 간의 고차상관관계를 표현하고, 베이지안 샘플링 알고리즘(Bayesian Sampling Algorithm)을 통해 다음 세대의 개체를 생성한다. 기만하는 빌딩블럭(deceptive building blocks)을 가진 분해가능(decomposable) 함수에 대하여 실험한 결과 성공적으로 최적해를 구할 수 있었으며 단순 유전자알고리즘과 BOA (Bayesian Optimization Algorithm)와 비교하여 좋은 성능을 얻을 수 있었다.

• 응용통계연구
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• 제27권2호
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• pp.239-247
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• 2014

본 논문에서는 사회적으로나 개인적으로 매우 민감한 조사에서 조사하고자 하는 모집단이 여러 개의 층으로 구성되어 있고, 각 층이 양적인 속성으로 되어 있는 경우에 Himmelfarb-Edgell의 가법 모형과 Gjestvang-Singh의 가법 모형에 단순임의추출법 대신에 층화추출법을 적용한 층화 가법 양적속성 확률화응답모형을 제안하였다. 제안한 두 모형으로부터 각 층의 양적속성에 대한 모평균의 추정뿐만 아니라 모집단 전체 모평균에 대한 추정을 할 수 있는 이론적 체계를 마련하였다. 그리고 제안한 두 모형에서 비례배분과 최적배분 문제를 다루었으며, 각 배분법에 따른 분산식을 도출하였다. 마지막으로 두 층화 가법 양적속성 확률화응답모형들 간의 효율성을 비교해 본 결과 Gjestvang-Singh의 층화 가법 모형이 Himmelfarb-Edgell의 층화 가법 모형보다 효율적으로 나타났고, 특히 hh값이 작을수록 즉, 제시한 모형의 특성이 직접질문에 가까워질수록 Gjestvang-Singh의 층화 가법 모형의 효율성이 커짐을 알 수 있었다.

• International Journal of Concrete Structures and Materials
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• 제18권2E호
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• pp.89-95
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• 2006

This paper proposes a modified method of Latin Hypercube sampling to reduce the variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This analysis method uses specifically modified tables of random permutations of ranked numbers. In addition, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. Statistical parameters obtained from modified Latin Hypercube sampling method and conventional Latin Hypercube sampling method are compared and evaluated by a numeric analysis. The results show that the proposed method results in a decrease in the variance of statistical parameters. This indicates the method is efficient and effective in the uncertainty analysis of complex structural system such as prestressed concrete bridges.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

• 한국해양공학회지
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• 제25권2호
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• pp.120-126
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• 2011

The fatigue damages in structural details of offshore plants can be accumulated due to various environmental loadings such as swell, wave, wind and current. It is known that load histories acting on mooring and riser systems show stationary and ergodic bimodal wide-banded process. This paper provides refined approach to obtain time signals representing stress range histories from wide-banded bimodal spectrum which consists of ideally narrow-banded and fully separated two spectrums. Variations of the probabilistic characteristics for time signals according to frequency and sampling time increments are compared with the reference data to be the probabilistic characteristics such as zero-crossing period, peak period, and irregularity factor obtained from an assumed ideal spectrum. It is proved that the sampling time increment more affects on the probabilistic characteristics than frequency increment. The fatigue damages according to the frequency and sampling time increments are also compared with the ones with minimum increment condition which are thought to be exact fatigue damage. It is concluded that the maximum sampling time increment to obtain reliable time signals should be determined that ratio of applied maximum sampling time increment and minimum period is less than approximately 0.08.