• 제목/요약/키워드: sample of random size

검색결과 201건 처리시간 0.026초

ASYMPTOTIC DEPENDENCE BETWEEN RANDOM CENTRAL QUASI-RANGES AND RANDOM EMPIRICAL QUANTILES

  • Nigm, E.M.
    • Journal of applied mathematics & informatics
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    • 제16권1_2호
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    • pp.289-302
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    • 2004
  • The asymptotic dependence between the central quasi-ranges and empirical quantiles was studied. The asymptotic dependence are obtained when the sample size is a positive integer valued random variable (r. v.). The dependence conditions and limit forms are obtained under generl conditions such as : the interrelation of the basic variables (the original random sample) and the random sample size is not restricted. In additition the normalizing constants do not depend on the random size.

계속조사에서 상대표준오차를 이용한 표본크기 결정에 관한 고찰 (A Note on the Decision of Sample Size by Relative Standard Error in Successive Occasions)

  • 한근식;이기성
    • 응용통계연구
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    • 제28권3호
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    • pp.477-483
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    • 2015
  • 본 연구에서는 계속조사에서 과거의 조사결과에서 얻은 추정값의 상대표준오차를 이용한 표본크기 결정 문제에 대하여 실제 사업체 조사자료를 활용하여 살펴보았다. 통계청 사업체 조사결과 중 건설업을 모집단으로 이용하여 표본크기를 500에서 3,000까지 500씩 증가시켜가면서 표본을 1,000개씩 단순임의추출 또는 층화추출하여 추출된 각 표본으로부터 상대표준오차들의 사분위수를 계산하였다. 그리고 이들 값들을 토대로 계속조사에서 시점 (t-1)에서의 상대표준오차를 이용한 시점 t에서의 표본크기를 추출법에 따라 구하였다. 그 결과 단순임의추출의 경우는 층화추출의 경우보다 시점 (t-1)에서의 상대표준오차들의 크기에 따라 표본크기가 매우 크게 차이가 나타남을 알 수 있었으며, 층화추출의 경우도 어떻게 층화를 하느냐에 따라 표본크기에 차이가 있을 수 있음을 알 수 있었다. 따라서 계속 조사에서 과거의 조사결과에서 얻은 추정값의 상대표준오차를 이용한 표본크기 식을 활용하는데 있어서 세심한 주의가 필요함을 확인할 수 있었다.

Numerical and statistical analysis of permeability of concrete as a random heterogeneous composite

  • Zhou, Chunsheng;Li, Kefei
    • Computers and Concrete
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    • 제7권5호
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    • pp.469-482
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    • 2010
  • This paper investigates the concrete permeability through a numerical and statistical approach. Concrete is considered as a random heterogeneous composite of three phases: aggregates, interfacial transition zones (ITZ) and matrix. The paper begins with some classical bound and estimate theories applied to concrete permeability and the influence of ITZ on these bound and estimate values is discussed. Numerical samples for permeability analysis are established through random aggregate structure (RAS) scheme, each numerical sample containing randomly distributed aggregates coated with ITZ and dispersed in a homogeneous matrix. The volumetric fraction of aggregates is fixed and the size distribution of aggregates observes Fuller's curve. Then finite element method is used to solve the steady permeation problem on 2D numerical samples and the overall permeability is deduced from flux-pressure relation. The impact of ITZ on overall permeability is analyzed in terms of ITZ width and contrast ratio between ITZ and matrix permeabilities. Hereafter, 3680 samples are generated for 23 sample sizes and 4 contrast ratios, and statistical analysis is performed on the permeability dispersion in terms of sample size and ITZ characteristics. By sample theory, the size of representative volume element (RVE) for permeability is then quantified considering sample realization number and expected error. Concluding remarks are provided for the impact of ITZ on concrete permeability and its statistical characteristics.

Nonresponse in Repeated Surveys

  • Park, Hyeon-Ah;Na, Seong-Ryong;Jeon, Jong-Woo
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.593-600
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    • 2007
  • Under repeated surveys, missing values often appear for various reasons and are replaced by new samples. It is investigated that the existing estimator in repeated survey by Jessen (1942), which has been originally developed for the new samples of fixed size, can be used in such situation where the size of new samples is random. It is shown that the proposed estimator has smaller variance than the sample mean.

Cluster Sampling in Sampling Inspection: Bayes Estimation

  • Juyoung Lee
    • Communications for Statistical Applications and Methods
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    • 제6권1호
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    • pp.107-116
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    • 1999
  • We propose a sample design which minimize Bayes risk for cluster smpling in sampling inspection. We treat a pilot sample and an additional sample size as random variable. In addition we compute an appropriate cluster size for handling over-dispersion.

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Estimating the Population Size from a Truncated Sample

  • Yeo, Sung-Chil
    • Journal of the Korean Statistical Society
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    • 제29권2호
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    • pp.169-185
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    • 2000
  • Given a random sample of size N (unknown) with density f(x│$\theta$), suppose that only n observations which lie outside a region r are recorded. On the basis of n observation, the Bayes estimators of $\theta$ and N are considered and their asymptotic expansions are developed to find the third order asymptotic properties with those of the maximum likelihood estimators and the Bayes modal estimators. The asymptotic m.s.e.'s of these estimators are expressed. An example is given to illustrate the results obtained.

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Mutual Information and Redundancy for Categorical Data

  • Hong, Chong-Sun;Kim, Beom-Jun
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.297-307
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    • 2006
  • Most methods for describing the relationship among random variables require specific probability distributions and some assumptions of random variables. The mutual information based on the entropy to measure the dependency among random variables does not need any specific assumptions. And the redundancy which is a analogous version of the mutual information was also proposed. In this paper, the redundancy and mutual information are explored to multi-dimensional categorical data. It is found that the redundancy for categorical data could be expressed as the function of the generalized likelihood ratio statistic under several kinds of independent log-linear models, so that the redundancy could also be used to analyze contingency tables. Whereas the generalized likelihood ratio statistic to test the goodness-of-fit of the log-linear models is sensitive to the sample size, the redundancy for categorical data does not depend on sample size but its cell probabilities itself.

Power of Variance Component Linkage Analysis to Identify Quantitative Trait Locus in Chickens

  • Park, Hee-Bok;Heo, Kang-Nyeong;Kang, Bo-Seok;Jo, Cheorun;Lee, Jun Heon
    • Journal of Animal Science and Technology
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    • 제55권2호
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    • pp.103-107
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    • 2013
  • A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

Modified partial least squares method implementing mixed-effect model

  • Kyunga Kim;Shin-Jae Lee;Soo-Heang Eo;HyungJun Cho;Jae Won Lee
    • Communications for Statistical Applications and Methods
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    • 제30권1호
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    • pp.65-73
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    • 2023
  • Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

적응집락추출에서 표본크기 결정과 추정량의 효율 비교 (Determination of Sample Size and Comparison of Efficiency in Adaptive Cluster Sampling)

  • 낭궁평;원혜경;최재혁
    • 응용통계연구
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    • 제20권3호
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    • pp.605-618
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    • 2007
  • 모집단 단위들이 희박하게 존재하고 접근하기 어려운 경우에 적용하는 적응추출설계에서의 추출과정은 관심변수의 관측값에 의존한다. 동일한 표본크기에서 적응집락추출의 추정량은 단순임의추출의 추정량에 비해 효율이 더 좋다 적응추출에서 Rao-blackwell의 정리를 적용하여 Murthy의 추정량의 형태로 수정한 한센-휴비_(HH) 추정량과 호르비_-톰슨 (HT) 추정량은 기존의 추정량에 비해 작은 분산을 가진다. 본 연구는 초기표본을 바꿔가면서 기대표본크기와 적응추출의 표본크기 하의 단순임의추출의 추정량과 적응추출의 추정량의 효율을 비교하였다.