• 응용통계연구
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• 제22권6호
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• pp.1289-1300
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• 2009

표본추출 비용의 절감을 위해 흔히 사용되는 이중표본추출방법은 대부분의 표본들이 2종류의 오류에 의해 오염이 되어 있어 통계적 분석이 상대적으로 용이하지 않다. 특히, 비율의 추론을 위한 중요한 분석 도구인 구간추정은 현재까지 우도추정량의 정규근사에 의존하는 Wald 방법만이 알려져 있으나 Wald 신뢰구간은 포함확률의 근사성 등에서 많은 문제가 있다는 것이 여러 연구에서 확인되고 있다. 본 연구에서는 이중표본추출에서 Wald 신뢰구간의 문제점을 파악하고 이에 대한 대안으로 Agresti-Coull 유형의 신뢰구간을 제시한다.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.

• Journal of the Korean Statistical Society
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• 제34권1호
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• pp.73-83
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• 2005

Thompson's (1990) adaptive cluster sampling is a promising sampling technique to ensure effective representation of rare or localized population units in the sample. We consider the problem of simultaneous estimation of the numbers of earners through a number of rural unorganized industries of which some are concentrated in specific geographic locations and demonstrate how the performance of a conventional Rao-Hartley-Cochran (RHC, 1962) estimator can be improved upon by using auxiliary information in the form of generalized regression (greg) estimators and then how further improvements are also possible to achieve by adopting adaptive cluster sampling.

• Communications for Statistical Applications and Methods
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• 제19권5호
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• pp.663-671
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• 2012

In the present study, a combined ratio cum regression estimator is proposed to estimate the population mean of the study variable in the presence of a non-response using an auxiliary variable under double sampling. The expressions of bias and mean squared error(MSE) based on the proposed estimator is derived under double (or two stage) sampling to the first degree of approximation. Some estimators are also derived from the proposed class by allocating the suitable values of constants used. A comparison of the proposed estimator with the usual unbiased estimator and other derived estimators is carried out. An empirical study is carried out to demonstrate the performance of the suggested estimator and of others; it is endow that the empirical results backing the theoretical study.

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.385-397
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• 2016

The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.

• 대한기계학회논문집A
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• 제31권1호
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• pp.55-61
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• 2007

Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

• 한국항공우주학회지
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• 제42권1호
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• pp.82-89
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• 2014

본 논문에서는 공진기 각진동에 의한 출력을 제거하기 위하여 복조방법을 사용하는 링레이저 자이로의 시간 양자화 오차를 감소시키기 위한 방법을 논의하였다. 링레이저 자이로에는 맥놀이 주파수를 검출하는 과정에서 발생하는 각도 양자화오차와 lock-in 현상을 해결하기 위하여 변조한 각진동을 출력으로부터 복조하는 과정에서 발생하는 시간 양자화오차가 있다. 시간 양자화 오차는 링레이저 자이로의 샘플링 주기가 자이로 각진동 주기에 동기된 복조방법을 사용하기 때문에 발생한다. 일반적으로 자이로 각진동 주기는 항법계산 주기에 비하여 길기 때문에, 탑재체의 자세를 빠른 속도로 업데이트 해야만 하는 고기동 환경에서는 시간양자화 오차에 의한 항법오차가 발생된다. 본 논문에서는 이러한 샘플링 시간 양자화오차를 줄이기 위하여 이중 복조방법을 제안하고, 시뮬레이션을 통하여 동적환경에서의 오차 감소현상을 확인하였다.

• 한국시뮬레이션학회논문지
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• 제9권2호
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• pp.75-87
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• 2000

In this paper, nonstationary multiple sampling plans are discussed which are difficult to solve by analytical method when there exists dependency between the sample data. The initial solution is found by the sequential sampling plan using the sequential probability ration test. The number of acceptance and rejection in each step of the multiple sampling plan are found by grouping the sequential sampling plan's solution initially. The optimal multiple sampling plans are found by simulation. Four search methods are developed U and the optimum sampling plans satisfying the Type I and Type ll error probabilities. The performance of the sampling plans is measured and their algorithms are also shown. To consider the nonstationary property of the dependent sampling plan, simulation method is used for finding the lot rejection and acceptance probability function. As a numerical example Markov chain model is inspected. Effects of the dependency factor and search methods are compared to analyze the sampling results by changing their parameters.

• 산업기술연구
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• 제3권
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• pp.27-32
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• 1983

This paper develops and provides formulas for calculating the Average Outgoing Quality and the Average Total Inspection for nine different sample/rest-of-lot disposition policies in which rectifying multiple sampling inspection by attribute can be carried out. The formulas are considered for perfect inspection as well as error-prone inspection.

• 대한전기학회논문지
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• 제45권4호
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• pp.530-534
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• 1996

A novel phase error predictor is proposed for servo system in home-use VCRs. The multirate system in VCRs is converted into a single period sampling system with faster sampling time by using the proposed novel phase error predictor. And the disturbances can be measured much faster. From the experimental results, we can see that the perfomance of the control system is improved greatly. The phase lock time of the proposed servo system is ten times faster than that of the conventional system.