• 제목/요약/키워드: ANOVA model

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Matching Conditions for Predicting the Random Effects in ANOVA Models

  • 장인홍
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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    • pp.1-6
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    • 2006
  • We consider the issue of Bayesian prediction of the unobservable random effects, And we characterize priors that ensure approximate frequentist validity of posterior quantiles of unobservable random effects. Finally we show that the probability matching criteria for prediction of unobservable random effects in one-way random ANOVA model.

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컴퓨터 그래픽스에 의한 이원 분산분석 (Computer graphics approach to two-way ANOVA)

  • 허문열
    • 응용통계연구
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    • 제8권1호
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    • pp.75-87
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    • 1995
  • 데이터 분석 과정에서 일부 데이터를 변화시키거나 또는 적용하고자 하는 통계적 모형의 성격을 변화시킬 때 이러한 변화가 분석 결과에 어떤 영향을 미치는가를 즉시에 알아보기 위해 동적그래픽스의 기법을 이용한다. 본 논문에서는 분산분석 과정을 동적그래픽스로 구현하는 방법과 이를 구현하는데 필요한 여러가지 형태의 플롯을 설명하고 이원 분산분석 모형에서 구현한 동적그래픽스 소프트웨어를 소개한다.

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근피로 중앙주파수를 위한 AR모델의 차수결정에 관한 연구 (A Study on Order Decision of AR Model for Median Frequency in Fatiguing EMG)

  • 조은석;차샘;이기영
    • 한국정보전자통신기술학회논문지
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    • 제3권1호
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    • pp.8-12
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    • 2010
  • 본 연구에서는 t-test와 ANOVA를 이용하여 근전도의 중앙주파수 추출을 위한 AR모델 차수결정 및 중앙주파수 비교에 관한 연구이다. 근전도의 근피로와 관계된 특징인자인 영교차율 및 저대역에너지, 중앙주파수를 추출하여 근피로에 이를 때까지의 변화를 평가해 봄으로써 근피로 정도나 시점까지의 변화 정도를 비교 및 고찰하였다.

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Predicting bond strength of corroded reinforcement by deep learning

  • Tanyildizi, Harun
    • Computers and Concrete
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    • 제29권3호
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    • pp.145-159
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    • 2022
  • In this study, the extreme learning machine and deep learning models were devised to estimate the bond strength of corroded reinforcement in concrete. The six inputs and one output were used in this study. The compressive strength, concrete cover, bond length, steel type, diameter of steel bar, and corrosion level were selected as the input variables. The results of bond strength were used as the output variable. Moreover, the Analysis of variance (Anova) was used to find the effect of input variables on the bond strength of corroded reinforcement in concrete. The prediction results were compared to the experimental results and each other. The extreme learning machine and the deep learning models estimated the bond strength by 99.81% and 99.99% accuracy, respectively. This study found that the deep learning model can be estimated the bond strength of corroded reinforcement with higher accuracy than the extreme learning machine model. The Anova results found that the corrosion level was found to be the input variable that most affects the bond strength of corroded reinforcement in concrete.

Optimization of static response of laminated composite plate using nonlinear FEM and ANOVA Taguchi method

  • Pratyush Kumar Sahu;Trupti Ranjan Mahapatra;Sanjib Jaypuria;Debadutta Mishra
    • Steel and Composite Structures
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    • 제48권6호
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    • pp.625-639
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    • 2023
  • In this paper, a Taguchi-based finite element method (FEM) has been proposed and implemented to assess optimal design parameters for minimum static deflection in laminated composite plate. An orthodox mathematical model (based on higher-order shear deformation plate theory and Green-Lagrange geometrical nonlinearity) has been used to compute the nonlinear central deflection values of laminated composite plates according to Taguchi design of experiment via a self-developed MATLAB computer code. The lay-up scheme, aspect ratio, thickness ratio and the support conditions of the laminated composite plate structure were designated as the governable design parameters. Analysis of variance (ANOVA) is used to investigate the effect of diverse control factors on the nonlinear static responses. Moreover, regression model is developed for predicting the desired responses. The ANOVA revealed that the lay-up scheme alongside the support condition plays vital role in minimizing the central deflection values of laminated composite plate under uniformly distributed load. The conformity test results of Taguchi analysis are also in good agreement with the numerical experimentation results.

3D 인쇄방법으로 제작된 치과용 다이 모델의 정확도 평가연구 (A study on the accuracy evaluation of dental die models manufactured by 3D printing method)

  • 장연
    • 대한치과기공학회지
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    • 제41권4호
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    • pp.287-293
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    • 2019
  • Purpose: To evaluate the accuracy of the 3D printed die models and to investigate its clinical applicability. Methods: Stone die models were fabricated from conventional impressions(stone die model; SDM, n=7). 3D virtual models obtained from the digital impressions were manufactured as a 3D printed die models using a 3D printer(3D printed die models;3DM, n=7). Reference model, stone die models and 3D printed die models were scanned with a reference scanner. All dies model dataset were superimposed with the reference model file by the "Best fit alignment" method using 3D analysis software. Statistical analysis was performed using the independent t-test and 2-way ANOVA (α=.05). Results: The RMS value of the 3D printed die model was significantly larger than the RMS value of the stone die model (P<.001). As a result of 2-way ANOVA, significant differences were found between the model group (P<.001) and the part (P<.001), and their interaction effects (P<.001). Conclusion: The 3D printed die model showed lower accuracy than the stone die model. Therefore, it is necessary to further improve the performance of 3D printer in order to apply the 3D printed model in prosthodontics.

Multi-Objective Optimization Using Kriging Model and Data Mining

  • Jeong, Shin-Kyu;Obayashi, Shigeru
    • International Journal of Aeronautical and Space Sciences
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    • 제7권1호
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    • pp.1-12
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    • 2006
  • In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).

3원 변량분석을 이용한 구분적으로 일정한 모델의 에너지 함수 최소화를 위한 매개변수들 추정 (The Estimation of Parameters to minimize the Energy Function of the Piecewise Constant Model Using Three-way Analysis of Variance)

  • 주기세;조덕상;서재형
    • 한국항행학회논문지
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    • 제16권5호
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    • pp.846-852
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    • 2012
  • 영상분할 결과는 알고리즘에 관련된 매개변수들에 따라 다르기 때문에 최적 분할을 위하여 시행 착오법이 많이 이용된다. 본 논문에서는 3차원 변량 분석법을 이용하여 영역기반 active contour 방법에 관련된 최적 매개변수들을 결정하는 방법을 제안한다. 3원 변량 분석법에 의해서 추출된 결과와 사용자가 영상에서 직접 그린 결과가 상호 비교된다. 마지막으로 각 매개변수들의 주요 효과와 상호작용 효과를 측정하고 최적 값을 추출하기 위하여 점 추정 및 구간 추정 값을 계산한다. 본 논문에서 제안한 방법은 구간 상수 모델을 대상으로 영상분할시 최적 매개변수들을 추출하는데 큰 도움을 줄 것이다.

Statistical Tests for Time Course Microarray Experiments

  • 박태성;이성곤;최호식;이승연;이용성
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 춘계 학술발표회 논문집
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    • pp.85-90
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    • 2002
  • Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time we are interested in testing gene expression profiles for different experimental groups. We propose a statistical test based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Using this test, we can detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

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Multiple Comparison for the One-Way ANOVA with the Power Prior

  • Bae, Re-Na;Kang, Yun-Hee;Hong, Min-Young;Kim, Seong-W.
    • Communications for Statistical Applications and Methods
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    • 제15권1호
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    • pp.13-26
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    • 2008
  • Inference on the present data will be more reliable when the data arising from previous similar studies are available. The data arising from previous studies are referred as historical data. The power prior is defined by the likelihood function based on the historical data to the power $a_0$, where $0\;{\le}\;a_0\;{\le}\;1$. The power prior is a useful informative prior for Bayesian inference such as model selection and model comparison. We utilize the historical data to perform multiple comparison in the one-way ANOVA model. We demonstrate our results with some simulated datasets under a simple order restriction between the treatments.