• 제목/요약/키워드: Bayesian model

검색결과 1,312건 처리시간 0.042초

Probabilistic real-time updating for geotechnical properties evaluation

  • Ng, Iok-Tong;Yuen, Ka-Veng;Dong, Le
    • Structural Engineering and Mechanics
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    • 제54권2호
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    • pp.363-378
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    • 2015
  • Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.

Estimation of Gini-Simpson index for SNP data

  • Kang, Joonsung
    • Journal of the Korean Data and Information Science Society
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    • 제28권6호
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    • pp.1557-1564
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    • 2017
  • We take genomic sequences of high-dimensional low sample size (HDLSS) without ordering of response categories into account. When constructing an appropriate test statistics in this model, the classical multivariate analysis of variance (MANOVA) approach might not be useful owing to very large number of parameters and very small sample size. For these reasons, we present a pseudo marginal model based upon the Gini-Simpson index estimated via Bayesian approach. In view of small sample size, we consider the permutation distribution by every possible n! (equally likely) permutation of the joined sample observations across G groups of (sizes $n_1,{\ldots}n_G$). We simulate data and apply false discovery rate (FDR) and positive false discovery rate (pFDR) with associated proposed test statistics to the data. And we also analyze real SARS data and compute FDR and pFDR. FDR and pFDR procedure along with the associated test statistics for each gene control the FDR and pFDR respectively at any level ${\alpha}$ for the set of p-values by using the exact conditional permutation theory.

바이어스필드에 의해 왜곡된 MRI 영상자료분할을 위한 EM 알고리즘 기반 접근법 (EM Algorithm-based Segmentation of Magnetic Resonance Image Corrupted by Bias Field)

  • 김승구
    • 응용통계연구
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    • 제16권2호
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    • pp.305-319
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    • 2003
  • 본 연구에서는 바이어스 필드에 의해 왜곡된 MRI 영상에 대한 분할을 위해 확장된 EM 알고리즘을 기반으로 한 통계적 접근법을 제시한다. 영상의 명암값을 자료로 하는 분할기법들은 고주파 성분의 잡음 뿐만 아니라 영상을 불균질하게 만드는 바이어스 필드라는 저주파 성분의 왜곡에 특히 취약하다. 이 문제를 해결하기 위해 본 논문에서는 잡음을 효과적으로 제어하기 위해 마코프랜덤필드가 적용된 정규혼합모형을 고려하며, 효과적인 바이어스 필드의 보정을 위해 페널티-우도를 도입하여 추정하는 방법으로 고안되었다.

Winbugs를 이용한 우리나라 주가지수의 변동성에 대한 추정 (Estimation of Volatility of Korea Stock Price Index Using Winbugs)

  • 김형민;장인홍;이승우
    • 통합자연과학논문집
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    • 제4권2호
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    • pp.121-129
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    • 2011
  • The purpose of this paper is to estimate the fluctuation of an earning rate and risk management using the price index of Korea stocks. After an observation of conception of fluctuation, we can show volatility clustering and fluctuation phenomenon in the Korea stock price index using GARCH model with heteroscedasticity. In addition, the effects of fluctuation on the time-series was evaluated, which showed the heteroscedasticity. MCMC method and Winbugs as Bayesian computation were used for analysis.

지속정찰 임무의 경로계획을 위한 불확실 기댓값 오리엔티어링 문제와 해법 (Orienteering Problem with Unknown Stochastic Reward to Informative Path Planning for Persistent Monitoring and Its Solution)

  • 김두영
    • 한국군사과학기술학회지
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    • 제22권5호
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    • pp.667-673
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    • 2019
  • We present an orienteering problem with unknown stochastic reward(OPUSR) model for persistent monitoring tasks with unknown event probabilities at each point of interest. Prior studies on orienteering problem for persistent monitoring task assume that rewards and event probabilities are known as a prior. In this paper, we propose a stochastic reward model with unknown event statistics and a path re-planning algorithm based on Bayesian reward inference. Experiments demonstrate the efficiency of our method.

Reliability based seismic fragility analysis of bridge

  • Kia, M.;Bayat, M.;Emadi, A.;Kutanaei, S. Soleimani;Ahmadi, H.R
    • Computers and Concrete
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    • 제29권1호
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    • pp.59-67
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    • 2022
  • In this paper, a reliability-based approach has been implemented to develop seismic analytical fragility curves of highway bridges. A typical bridge class of the Central and South-eastern United States (CSUS) region was selected. Detailed finite element modelling is presented and Incremental Dynamic Analysis (IDA) is used to capture the behavior of the bridge from linear to nonlinear behavior. Bayesian linear regression method is used to define the demand model. A reliability approach is implemented to generate the analytical fragility curves and the proposed approach is compared with the conventional fragility analysis procedure.

Different estimation methods for the unit inverse exponentiated weibull distribution

  • Amal S Hassan;Reem S Alharbi
    • Communications for Statistical Applications and Methods
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    • 제30권2호
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    • pp.191-213
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    • 2023
  • Unit distributions are frequently used in probability theory and statistics to depict meaningful variables having values between zero and one. Using convenient transformation, the unit inverse exponentiated weibull (UIEW) distribution, which is equally useful for modelling data on the unit interval, is proposed in this study. Quantile function, moments, incomplete moments, uncertainty measures, stochastic ordering, and stress-strength reliability are among the statistical properties provided for this distribution. To estimate the parameters associated to the recommended distribution, well-known estimation techniques including maximum likelihood, maximum product of spacings, least squares, weighted least squares, Cramer von Mises, Anderson-Darling, and Bayesian are utilised. Using simulated data, we compare how well the various estimators perform. According to the simulated outputs, the maximum product of spacing estimates has lower values of accuracy measures than alternative estimates in majority of situations. For two real datasets, the proposed model outperforms the beta, Kumaraswamy, unit Gompartz, unit Lomax and complementary unit weibull distributions based on various comparative indicators.

Arbitrator's Reputation and PR Cost: A Signaling Approach

  • Joon Yeop Kwon;Sung Ryong Kim
    • 한국중재학회지:중재연구
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    • 제33권3호
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    • pp.129-146
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    • 2023
  • We construct a signaling game model between the arbitrator and claimants, in which the arbitrator's marketing amount is adopted as the signaling device. Assuming that the parties to the dispute select an arbitrator, and if there is a difference in the arbitrator's fee depending on the arbitrator's reputation, the arbitrator will pay to further enhance his reputation. We would like to analyze the cost differences between arbitrators who already have a high reputation and arbitrators who strive to further enhance their reputation using the signal model. From the Analysis of our study, We derive perfect Bayesian equilibrium of the signaling game and refine the equilibrium into a unique equilibrium by invoking the Intuitive Criterion of Cho and Kreps (1987). Further, we characterize the refined equilibrium.

향어(Cyprinus carpio nudus)의 Myxobolus artus 국내 첫 감염사례 보고 (First report on Myxobous artus infection in leather carp (Cyprinus carpio nudus) in Korea)

  • 송준영;김아란
    • 한국어병학회지
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    • 제36권2호
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    • pp.409-414
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    • 2023
  • Ellipsoidal-shaped spores with two polar capsules were detected in leather carp (Cyprinus carpio nudus) muscle. 18S rDNA gene analysis of the spore showed a 99.58% match to Myxobolus artus, a myxozoan parasite. As a result of phylogenetic analysis using the Bayesian inference model and maximum likelihood model among other Myxobolus species, the isolate in the present study belonged to the M. artus cluster. This is the first case report of M. artus infection detected in domestic aquaculture organisms in Korea.

신병 주특기교육 성취집단 예측모형 개발 (Development of newly recruited privates on-the-job Training Achievements Group Classification Model)

  • 곽기효;서용무
    • 한국국방경영분석학회지
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    • 제33권2호
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    • pp.101-113
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    • 2007
  • 국방부에서 발표한 '국방개혁에 관한 법률'에 따라 2014년까지 현역병들에 대한 복무기간이 단계적으로 단축될 예정이다. 이에 따라 육군에서는 좀 더 효율적인 직무교육 방안의 일환으로 훈련병들에게 '차등제 교육'을 시행하고 있다. 이러한 차등제 교육의 효과를 향상시키기 위해서는 훈련병들의 예상 학업 성취도를 미리 예측하여 성취집단별로 차별화 된 교육과정을 거치게 하는 것이 매우 중요하다. 따라서 본 연구에서는 입교초기에 얻을 수 있는 신병들의 제한된 자료들만을 이용하여 그들의 예상 교육 성취집단을 예측하는 모형을 개발하였다. 본 모형의 목적 변수는 '성취집단'이며 '일반관리 인원' 및 '집중관리 인원'의 두 가지 값을 갖는다. 사용된 기법은 인공신경망(Neural Network) 모형, 의사결정나무(Decision Tree) 모형, SVM 모형, 그리고 Naive Bayesian모형 등 4가지 순수 모형과, 각각의 순수 모형을 k-means군집기법과 혼합한 4가지의 혼합모형 등 총 8개의 모형의 성능을 비교 분석하였다. 실험 결과 k-means군집기법과 인공신경망 기법을 혼합한 모형이 가장 좋은 예측력을 보이는 것으로 나타났다. 이러한 교육 성취집단 예측 모형은 향후 군에서 이루어지는 다양한 교육 프로그램에 효과적으로 이용될 수 있을 것으로 기대된다.