• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.443-449
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• 2017

Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.

• Earthquakes and Structures
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• 제23권2호
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• pp.115-128
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• 2022

One common method to select input ground motions to predict dynamic behavior of structures subjected to seismic excitation requires spectral acceleration (S_a) match target mean response spectrum. However, dispersion of ground motions, which explicitly affects the structural response, is rarely discussed in this method. Generally, selecting ground motions matching target mean and variance has been utilized as an appropriate method to predict reliable seismic response. The goal of this paper is to investigate the impact of target spectra variance of ground motions on structural seismic response. Two sets of ground motions with different target variances (zero variance and minimum variance larger than inherent variance of the target spectrum) are selected as input to two different structures. Structural responses at different heights are compared, in terms of peak, mean and dispersion. Results show that increase of target spectra variance tends to increase peak floor acceleration, peak deformation and dispersions of response of interest remarkably. To short-period structures, dispersion increase ratios of seismic response are close to that of S_a of input ground motions at the first period. To long-period structures, dispersions of floor acceleration and floor response spectra increase more significantly at the bottom, while dispersion increase ratios of IDR and deformation are close to that of S_a of input ground motions at the first period. This study could further provide useful information on selecting appropriate ground motion to predict seismic behavior of different types of structures.

• 응용통계연구
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• 제14권1호
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• pp.13-24
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• 2001

이중추출에서 모평균 추정방법을 고찰하였다. 전통적으로 널리 쓰이는 비추정량과 회귀추정량 그리고 비례배분 및 Rao 배분을 한 후의 층화평균에 대하여 주어진 기대 비용에서 최적의 표본수, 최소분산 및 분산추정량을 살펴보았다. 또한 비추정 및 층화의 효과를 모두 내포하는 결합비 추정량을 제안하고 주어진 기대 비용에서 최적의 표본수 및 최소분산을 유도하였고 분산추정량을 구하였다. 그리고 제한된 모의실험을 통하여 비추정량, 층화평균 및 결합비 추정량의 효율을 비교하였다. 모의실험 결과 비추정량과 층화평균은 경우에 따라 효율이 다르게 나타난 반면, 결합비 추정량은 대체로 두 방법보다 효율이 우수하게 나타나 결합비 추정량이 이중추출에 유용하게 쓰일 수 있음을 보였다.

• 품질경영학회지
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• 제22권4호
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• pp.1-12
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• 1994

각각의 설계인자들의 실험조건에서 얻어지는 특성치들의 분산은 평균에 영향을 받는다. 많은 경우에 평균이 커짐에 따라서 분산이 커지는 경향이 있다. 다구찌가 산포제어인자를 찾기 위해서 제시한 SN 비인 $(SN)_i$ = 10 log ($\bar{y}_{i}^{2}/s_{i}^{2}$) 은 분산이 평균의 제곱에 비례하여 커지는 경우이다. 그런데 분산이 평균의 제곱보다 더 느리게 또는 더 빠르게 커질 수도 있기 때문에 이 논문에서는 간단한 자료분석적 기법에 의해서 그 관계를 추측하여, 합당한 SN 비를 사용할 것을 제시하였고, 평균조정인자를 찾기위한 통계량인 감도 $(S)_i$ 의 통계적 성질들을 논의하였다.

• 품질경영학회지
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• 제30권1호
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• pp.118-132
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• 2002

This paper presents a process incapability index to provide manager with various information of process and to reduce cost. The introduced process incapability indices indicate information about mean and variance of manufacturing process and variance of inspection process to evaluate process capability using ratio of variance and difference between target and mean to specification. This model can be used by the scale of six sigma management.

• 한국정밀공학회지
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• 제12권5호
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• pp.98-107
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• 1995

The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

• 한국국방경영분석학회지
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• 제28권1호
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• pp.47-66
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• 2002

Instead of using signal-to-noise ratio, we attempt to optimize both the mean and variance responses using dual response optimization technique. The alternative experimental strategy analyzes a robust parameter design problem to obtain the best settings that give a target condition on the mean while minimizing its variance. The mean and variance are treated as the two responses of interest to be optimized. Unlike to the crossed array and combined array approaches, our experimental setup requires replicated runs for each control factor's treatment under noise sampling. When the postulated response models are true, they enable the coefficients to be estimated and the desired performance measure to be analyzed more efficiently. The procedure and illustrative example are given for the dual response optimization techniques of nonlinear goal programming.

• Journal of Communications and Networks
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• 제16권6호
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• pp.583-591
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• 2014

In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

• 품질경영학회지
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• 제29권1호
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• pp.47-61
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• 2001

The ever increasing demands for enhanced competitiveness of engineered products require a "designing-in-quality" strategy that can effectively and efficiently incorporate multiple design objectives into design. Robust design can be viewed as a multi-characteristic design problem requiring tradeoffs between mean and variance characteristics. Firstly this paper analyzes the intrinsic preference of the traditional SN ratio on mean and variance, and secondly presents a new design metric for a robust design using concepts from utility theory to accurately capture designer′s intent and preference on mean and variance. The steps to apply the proposed design metric as the robust design criterion in an orthogonal array based engineering experimentation is presented with the aid of a demonstrative case study. The performance of the proposed design metric is tested, and the results are discussed.

• Journal of the Korean Data and Information Science Society
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• 제20권3호
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• pp.577-585
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• 2009

So far in a nonparametric regression model one of the interesting problems is estimating the error variance. In this paper we propose an estimator of the mean of the squared functions which is the numerator of SNR (Signal to Noise Ratio). To estimate SNR, the mean of the squared function should be firstly estimated. Our focus is on estimating the amplitude, that is the mean of the squared functions, in a nonparametric regression using a simple linear regression model with the quadratic form of observations as the dependent variable and the function of a lag as the regressor. Our method can be extended to nonparametric regression models with multivariate functions on unequally spaced design points or clustered designed points.