• 제목/요약/키워드: Variance Analysis

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망목특성에서의 자료분석을 통한 SN비의 선택 (Selection of Signal-to-Noise Ratios through Simple Data Analysis)

  • 임용빈
    • 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.

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통계적 실험계획 및 분석: Gate Poly-Silicon의 Critical Dimension에 대한 계층적 분산 구성요소 및 웨이퍼 수준 균일성 (Statistical Design of Experiments and Analysis: Hierarchical Variance Components and Wafer-Level Uniformity on Gate Poly-Silicon Critical Dimension)

  • 박성민;김병윤;이정인
    • 대한산업공학회지
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    • 제29권2호
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    • pp.179-189
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    • 2003
  • Gate poly-silicon critical dimension is a prime characteristic of a metal-oxide-semiconductor field effect transistor. It is important to achieve the uniformity of gate poly-silicon critical dimension in order that a semiconductor device has acceptable electrical test characteristics as well as a semiconductor wafer fabrication process has a competitive net-die-per-wafer yield. However, on gate poly-silicon critical dimension, the complexity associated with a semiconductor wafer fabrication process entails hierarchical variance components according to run-to-run, wafer-to-wafer and even die-to-die production unit changes. Specifically, estimates of the hierarchical variance components are required not only for disclosing dominant sources of the variation but also for testing the wafer-level uniformity. In this paper, two experimental designs, a two-stage nested design and a randomized complete block design are considered in order to estimate the hierarchical variance components. Since gate poly-silicon critical dimensions are collected from fixed die positions within wafers, a factor representing die positions can be regarded as fixed in linear statistical models for the designs. In this context, the two-stage nested design also checks the wafer-level uniformity taking all sampled runs into account. In more detail, using variance estimates derived from randomized complete block designs, Duncan's multiple range test examines the wafer-level uniformity for each run. Consequently, a framework presented in this study could provide guidelines to practitioners on estimating the hierarchical variance components and testing the wafer-level uniformity in parallel for any characteristics concerned in semiconductor wafer fabrication processes. Statistical analysis is illustrated for an experimental dataset from a real pilot semiconductor wafer fabrication process.

Complex Segregation Analysis of Total Milk Yield in Churra Dairy Ewes

  • Ilahi, Houcine;Othmane, M. Houcine
    • Asian-Australasian Journal of Animal Sciences
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    • 제24권3호
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    • pp.330-335
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    • 2011
  • The mode of inheritance of total milk yield and its genetic parameters were investigated in Churra dairy sheep through segregation analyses using a Monte Carlo Markov Chains (MCMC) method. Data which consisted of 7,126 lactations belonging to 5,154 ewes were collected between 1999 and 2002 from 15 Spanish Churra dairy flocks. A postulated major gene was assumed to be additive and priors used for variance components were uniform. Based on 50 000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated marginal posterior means${\pm}$posterior standard deviations of variance components of milk yield were $23.17{\pm}18.42$, $65.20{\pm}25.05$, $120.40{\pm}42.12$ and $420.83{\pm}40.26$ for major gene variance ($\sigma_G^2$), polygenic variance ($\sigma_u^2$), permanent environmental variance ($\sigma_{pe}^2$) and error variance ($\sigma_e^2$), respectively. The results of this study showed the postulated major locus was not significant, and the 95% highest posterior density regions ($HPDs_{95%}$) of most major gene parameters included 0, and particularly for the major gene variance. The estimated transmission probabilities for the 95% highest posterior density regions ($HPDs_{95%}$) were overlapped. These results indicated that segregation of a major gene was unlikely and that the mode of inheritance of total milk yield in Churra dairy sheep is purely polygenic. Based on 50,000 Gibbs samples from ten replicates chains of 100,000 cycles, the estimated polygenic heritability and repeatability were $h^2=0.20{\pm}0.05$ and r=$0.34{\pm}0.06$, respectively.

개인, 교육기관, 사회적 변인이 사이버대 재학생의 중도탈락의도 결정에 미치는 영향 (The Effects of Personal, Institutional, Social Variables on Determination of The Cyber University Students' Dropout Intention)

  • 권혜진
    • 한국콘텐츠학회논문지
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    • 제10권3호
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    • pp.404-412
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    • 2010
  • 본 연구는 사이버대학생의 개인적 변인, 교육기관 변인, 사회적 변인이 중도탈락의도 결정에 미치는 영향을 알아봄으로 사이버대학생의 중도탈락동기를 낮추고 학업 지속 환경을 조성하는데 기초 자료를 제시하고자 하였다. 이를 위하여 A사이버대학에 재학생을 대상으로 편의 표집법(convenience sampling)을 이용하여 2009년 4월 1일부터 5월 31일까지 500명에게 설문을 의뢰하였다. 수집된 336명의 자료 중 응답내용이 불성실하다고 판단되거나 중다반응으로 유효하지 않은 자료 총 32명 응답분량을 제외하여 본 연구에서는 총 304부를 분석에 사용하였다. 자료분석은 SPSS for Winow 15.0을 활용하여 로지스틱 회귀분석을 실시하였다. 연구결과 첫째, 개인의 흥미변인이 중도탈락 의도에 영향을 주는 것으로 나타났다. 둘째, 교육기관 환경적 변인이 중도탈락 의도에 영향을 주는 것으로 나타났다. 셋째, 사회적 환경변인이 중도탈락 의도에 영향을 주는 것으로 나타났다. 넷째, 개인, 교육기관, 사회적 변인이 사이버 대학생의 중도탈락 의도에 미치는 영향 중 개인 변인만이 통계적으로 유의미하게 중도탈락 의도를 결정하지 않게 하는 데 유의미한 영향을 주는 것으로 나타났다.

무정보 사전분포를 이용한 이원배치 혼합효과 분산분석모형에서 오차분산에 대한 베이지안 분석 (Bayesian Analysis for the Error Variance in a Two-Way Mixed-Effects ANOVA Model Using Noninformative Priors)

  • 장인홍;김병휘
    • 응용통계연구
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    • 제15권2호
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    • pp.405-414
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    • 2002
  • 반복이 같은 이원배치 혼합효과 분산분석모형에서 무정보 사전분포를 이용하여 오차분산을 추정하는 문제를 생각하고자 한다. 먼저 무정보 사전분포로 제프리스사전분포, 준거 사전분포 그리고 확률일치 사전분포를 유도하고 이들 각각의 사전분포들에 대하여 주변사후분포를 제시하였다. 끝으로 실제 자료를 근거로 오차분산의 주변사후밀도함수에 대한 그래프와 오차분산에 대한 신용구간들을 구하고 이 구간들을 비교한다.

Analysis of inconsistent source sampling in monte carlo weight-window variance reduction methods

  • Griesheimer, David P.;Sandhu, Virinder S.
    • Nuclear Engineering and Technology
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    • 제49권6호
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    • pp.1172-1180
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    • 2017
  • The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS) method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

기술발전에 따른 생존모형 선정 (Selection of Survival Models for Technological Development)

  • 오현승;김종수;이한교;임동순;조진형
    • 산업경영시스템학회지
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    • 제32권4호
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    • pp.184-191
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    • 2009
  • In a technological driven environment, a depreciation estimate which is based on traditional life analysis results in a decelerated rate of capital recovery. This time pattern of technological growths models needs to be incorporated into life analysis framework especially in those industries experiencing fast technological changes. The approximation technique for calculating the variance can be applied to the six growth models that were selected by the degree of skewness and the transformation of the functions. For the Pearl growth model, the Gompertz growth model, and the Weibull growth model, the errors have zero mean and a constant variance over time. However, transformed models like the linearized Fisher-Pry model, the linearized Gompertz growth model, and the linearized Weibull growth model have increasing variance from zero to that point at which inflection occurs. It can be recommended that if the variance of error over time is increasing, then a transformation of observed data is appropriate.

Condition assessment of bridge pier using constrained minimum variance unbiased estimator

  • Tamuly, Pranjal;Chakraborty, Arunasis;Das, Sandip
    • Structural Monitoring and Maintenance
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    • 제7권4호
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    • pp.319-344
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    • 2020
  • Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

A STOCHASTIC VARIANCE REDUCTION METHOD FOR PCA BY AN EXACT PENALTY APPROACH

  • Jung, Yoon Mo;Lee, Jae Hwa;Yun, Sangwoon
    • 대한수학회보
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    • 제55권4호
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    • pp.1303-1315
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    • 2018
  • For principal component analysis (PCA) to efficiently analyze large scale matrices, it is crucial to find a few singular vectors in cheaper computational cost and under lower memory requirement. To compute those in a fast and robust way, we propose a new stochastic method. Especially, we adopt the stochastic variance reduced gradient (SVRG) method [11] to avoid asymptotically slow convergence in stochastic gradient descent methods. For that purpose, we reformulate the PCA problem as a unconstrained optimization problem using a quadratic penalty. In general, increasing the penalty parameter to infinity is needed for the equivalence of the two problems. However, in this case, exact penalization is guaranteed by applying the analysis in [24]. We establish the convergence rate of the proposed method to a stationary point and numerical experiments illustrate the validity and efficiency of the proposed method.

Optimum seat design for the quadruple offset butterfly valve by analysis of variance with orthogonal array

  • Lee, Sang-Beom;Lee, Dong-Myung
    • Journal of Advanced Marine Engineering and Technology
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    • 제38권8호
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    • pp.961-967
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    • 2014
  • In onshore and offshore plant engineering, a broad use of pipe system have been achieved and accordingly related technologies has been developed especially in the field of flow control valves. The aim of this study is to suggest the quadruple offset butterfly valve for bi-directional applications which show equivalent operating torque characteristics of the triple offset butterfly valve. Seat design parameters for the quadruple offset butterfly valve are determined by the proposed method utilizing both ANOVA (analysis of variance) and the orthogonal array. Through additive model considering the effect of design parameters on seating torque, mean estimation is performed and thus its optimization results are verified by design of experiment results. The insight obtained from the present study is beneficial for valve design engineers to develop reliable and integrated design of the quadruple offset butterfly valve.