• 대한안전경영과학회지
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• 제9권2호
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• pp.161-169
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• 2007

This paper presents three methods for expression of reliability measures for large and small data. First method is to express parametric estimation of cardinal reliability measure data for large sample, which requires numerous sample. Second is to obtain nonparametric distribution classification of ordinal reliability measure data for small sample. However it is difficult for field user to understand this method. Last method is to acquire parametric estimation of ordinal reliability measure data for small data. Because this method requires small sample and is comprehensive, we recommend this one among the proposed methods. Various reliability rank measures are presented.

• 통합자연과학논문집
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• 제14권3호
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• pp.123-129
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• 2021

This research examines the effect of positively skewed population distribution on the two sample t-test through simulation. For simulation work, two independent samples were selected from the same chi-square distributions with 3, 5, 10, 15, 20, 30 degrees of freedom and sample sizes 3, 5, 10, 15, 20, 30, respectively. Chi-square distribution is largely skewed to the right at small degrees of freedom and getting symmetric as the degrees of freedom increase. Simulation results show that the sampled populations are distributed positively skewed like chi-square distribution with small degrees of freedom, the F-test for the equality of variances shows poor performances even at the relatively large degrees of freedom and sample sizes like 30 for both, and so it is recommended to avoid using F-test. When two population variances are equal, the skewness of population distribution does not affect on the t-test in terms of the confidence level. However even though for the highly positively skewed distribution and small sample sizes like three or five the t-test achieved the nominal confidence level, the error limits are very large at small sample size. Therefore, if the sampled population is expected to be highly skewed to the right, it will be recommended to use relatively large sample size, at least 20.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.407-416
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• 2001

Sample surveys are usually designed and analyzed to produce estimates for a large area or populations. Therefore, for the small area estimations, sample sizes are often not large enough to give adequate precision. Several small area estimation methods were proposed in recent years concerning with sample sizes. Here, we will compare simple Bayesian approach with Bayesian prediction for small area estimation based on linear regression model. The performance of the proposed method was evaluated through unemployment population data form Economic Active Population(EAP) Survey.

• 대한전자공학회논문지SP
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• 제46권2호
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• pp.78-88
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• 2009

본 논문에서는 LDA를 이용한 얼굴 인식에서 발생하는 small sample size 문제를 해결하기 위한 효율적인 방법인 resampling 방법을 제안한다. 기존에는 regularization method를 사용하여 small sample size 문제를 해결하였는데, 이 방법을 사용하면 클래스내 분산행렬의 특이성을 없앨 수 있지만, 클래스내 분산행렬과 상수를 곱하는 과정에서 상수 값을 임의로 정해 주어야 하고, 이 상수 값에 따라 인식률이 개선되지 않을 수 있다는 문제점이 발생한다. 제안된 resampling 방법을 이용하여 학습 데이터의 수를 늘리면, regularization method보다 개선된 인식률을 얻을 수 있고, 또한 경험적으로 상수 값을 지정해 주는 과정을 거치지 않아도 되는 장점이 있다.

• 응용통계연구
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• 제15권2호
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• pp.297-310
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• 2002

Liang과 Zeger는 이산형 혹은 연속형 반복측정자료를 분석하기 위한 일반화 추정방정식 (GEE)을 제안하였다 GEE모형은 범주형 반복측정자료의 모형으로 확장될 수 있으며, 이 GEE추정량은 대표본인 경우 다변량 정규분포를 따른다. 그러나 GEE는 대표본근사이론에 기초한다. 본 논문에서는 소표본인 경우 반복 측정된 순서자료에 대한 GEE추정량의 성질을 연구한다. 우리는 두가지 방법을 사용하여 두그룹의 반복 측정된 순서자료를 생성하며 모의실험을 통하여 소표본인 경우 여러 개 범주를 갖는 순서반응 자료에 대하여 GEE추정량의 1종 오류율, 검정력, 상대효율, 두 그룹의 표본크기가 다를 경우 효과, 그리고 분산 추정량의 성질등을 연구한다.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1223-1232
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• 2011

Tong and Wang's estimator (2005) is a new approach to estimate the error variance using least squares method such that a simple linear regression is asymptotically derived from Rice's lag- estimator (1984). Their estimator highly depends on the setting of a regressor and weights in small sample sizes. In this article, we propose a new approach via a local quadratic approximation to set regressors in a small sample case. We estimate the error variance as the intercept using a ridge regression because the regressors have the problem of multicollinearity. From the small simulation study, the performance of our approach with some existing methods is better in small sample cases and comparable in large cases. More research is required on unequally spaced points.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.1109-1114
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• 2008

To investigate the effect of sample size on coefficient of consolidation of non-homogeneous soil, the result of a large size consolidation test using a huge undisturbed sample with $1200mm(D){\times}2000mm(H)$ in dimension is compared with that of oedometer test using undisturbed small sample. In addition, test results are compared with those of same test using remold sample. Experimental results show that, due to the lump of sand/silt was mixed in sample, the coefficient of consolidation of undisturbed samples have a difference for each tests. Whereas, the difference of coefficient of consolidation between remolded large and small samples is not found. Because sample size affects the test results, sample must be carefully selected for non-homogeneous soil.

• 통합자연과학논문집
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• 제12권3호
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• pp.91-99
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• 2019

Many researchers in various study fields use the two sample t-test to confirm their treatment effects. The two sample t-test is generally used for small samples, and assumes that two independent random samples are selected from normal populations, and the population variances are unknown. Researchers often conduct F-test, the test of equality of variances, before testing the treatment effects, and the test statistic or confidence interval for the two sample t-test has two formats according to whether the variances are equal or not. Researchers using the two sample t-test often want to know how large sample sizes they need to get reliable test results. This research gives some guidelines for sample sizes to them through simulation works. The simulation had run for normal populations with the different ratios of two variances for different sample sizes (${\leq}30$). The simulation results are as follows. First, if one has no idea equality of variances but he/she can assume the difference is moderate, it is safe to use sample size at least 20 in terms of the nominal level of significance. Second, the power of F-test for the equality of variances is very low when the sample sizes are small (<30) even though the ratio of two variances is equal to 2. Third, the sample sizes at least 10 for the two sample t-test are recommendable in terms of the nominal level of significance and the error limit.

• 대한산업공학회지
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• 제41권1호
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• pp.115-120
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• 2015

Evaluating product quality level is necessary before the manufactured items are delivered to the customer. When the amount of the items to be manufactured is limited and the product is of high price and should be evaluated by destructive testing, the number of samples to be tested should be as small as possible. This paper presents a small-sample inspection method using hyper-geometric distribution and Bayesian approach for finite small-sized population. A method of determining the minimum sample size is presented for given population size, allowable number of defectives, warranteed defective level, and confidence level which is the degree of confidence on the product quality level recognized by both the producer and the customer.

• 응용통계연구
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• 제11권2호
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• pp.287-302
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• 1998

표본평균(sample mean)의 밀도함수(density function)와 분포함수(distribution function)에 대한 안부점 근사(saddlepoin\ulcorner approximation)는 Daniels(1954, 1987), Lugannani와 Rice(1980)등에 의하여 유도되었으며, 이 근사식들의 정확도는 대표본(large sample)의 경우는 물론 소표본(small sample)의 경우에도 매우 뛰어난 것으로 알려져 있다. 최근 Easton과 Ronchetti(1986)는 일반적 통계량(general statistics)의 밀도함수에 대한 안부점 근사법을 제안하였고, 분포함수에 대한 근사로는 밀도함수에 대한 안부점 근사식을 직접 수치적으로 적분하는 방법을 제안하였다. 본 논문에서는 일반적 통계량의 분포함수에 대한 안부점 근사법을 제안하고, 이를 표본분산(sample variance)과 스튜던트화 평균(studentizd mean)의 분포함수에 대한 근사에 적용하였다.