• 제목/요약/키워드: model selection

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Sensitivity analysis in Bayesian nonignorable selection model for binary responses

  • Choi, Seong Mi;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.187-194
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    • 2014
  • We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

e-Business 환경 하에서 ISO 9001 품질경영시스템의 효율적인 공급자 선정모델 (An effective Supplier Selection Model for e-Business & ISO 9001 System)

  • 이무성;이영해
    • 품질경영학회지
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    • 제30권4호
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    • pp.15-25
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    • 2002
  • This paper considers supplier selection process for e-business & ISO 9001 quality management system environments. Determining suitable suppliers in the electronic commerce has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In this paper, a Quality Estimated Supplier Selection (QESS) model is proposed to deal with the supplier selection problems in the e-business(Business to Business: B to B). In the supplier selection, quality management factors will be considered for the first time, and then price, and delivery etc. In the first level, we deal with the quality management factors such as quality management audit, product test, engineering man-power, capability index and training time etc., based on the five point scale. In the second level, a QESS model determines the final solution by considering factors such as price, production lead-time and delivery time.

Bayesian Model Selection in the Gamma Populations

  • Kang, Sang-Gil;Kang, Doo-Young
    • Journal of the Korean Data and Information Science Society
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    • 제17권4호
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    • pp.1329-1341
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    • 2006
  • When X and Y have independent gamma distributions, we consider the testing problem for two gamma means. We propose a solution based on a Bayesian model selection procedure to this problem in which no subjective input is considered. The reference prior is derived. Using the derived reference prior, we compute the fractional Bayes factor and the intrinsic Bayes factors. The posterior probability of each model is used as a model selection tool. Simulation study and a real data example are provided.

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목표계획법을 이용한 사단급 ASL선정모형에 관한 연구 (A Study on the Authorized Stockage List Slection Model Using Goal Programing)

  • 길계호;김충영
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1998년도 추계학술대회 논문집
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    • pp.75-78
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    • 1998
  • The selection criteria of the Authorized Stockage List(ASL) in the Army is based on Army Regulation(AR)409, the selection method of ASL is not considered in cost, weight and volume of repair parts. This paper is focused on developing for a new selection model taking account of cost, weight and volume of repair parts. This model is applied to data of a division. The ASL selected in the model is more reduced in cost, weight and volume than that of the previous method.

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Hybrid Case-based Reasoning and Genetic Algorithms Approach for Customer Classification

  • Kim Kyoung-jae;Ahn Hyunchul
    • Journal of information and communication convergence engineering
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    • 제3권4호
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    • pp.209-212
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    • 2005
  • This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

국민학교(國民學校) 과학영재(科學英才) 선발(選拔) 준거(準據)에 관(關)한 연구(硏究) (A Study on the Selection Criteria of Science Gifted Children)

  • 서형두;정완호
    • 한국과학교육학회지
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    • 제13권2호
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    • pp.172-186
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    • 1993
  • This stady was carried out to define Gifted student for science, model for selection, the tools and methods and related theory for the selection of the Gifted students for the science in primary school level. Also the developed tools and materials are applied to student and analysed the results to generalize the methods for the selection of Gifted students for science. The definition of Gifted students for science was carried out by the three-ring conception model by Renzulli(1982) and Lee long-Sung which defined the characteristics as three parts such as above average ability, creativity and tesk comitment. The Gifted students for science upper 2 percent which have three characteristics at the same times, namely overlapping three characteristics. The model for the selection of Gifted students consist of four step; such as screeing, selection,differentiation, judgement. The materials for the selection are input at each stage, analysed the results and standard for the selection are made. In the first stage screening, 202 students are selected from the 5060 of 4th and 5th graders according to their achievment, intellecture ability and observation of students activity. In second selection and third differentiation stage, 65 students are seletted according to their achievement In this study it is approved that the Gifted students in science have to be selection by various test such as achievement, intellectual ability, aptitude in science, inquiry activity, manual skill etc, rather rather then simple test such as achievement and intellecture ability. Also it is important to select upper 2 percent who have general abilites overlapping three characteristics mentioned in definition of Gifted students in science and selections model

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베이지안 로지스틱 회귀모형에서의 추론에 대한 연구 (Inferential Problems in Bayesian Logistic Regression Models)

  • 황진수;강성찬
    • 응용통계연구
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    • 제24권6호
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    • pp.1149-1160
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    • 2011
  • 기존의 frequentist 추론에 비해 Bayesian 추론에서의 가설 검정 및 모형 선택 문제는 학자들 간에 일치된 견해를 보이지 못하고 있으며 아직도 논란이 되는 것들이 많다. Bayesian 추론에서 가설 검정 및 모형 선택의 기준으로 널리 쓰이는 Bayes factor는 이해하기 쉬우나 여러 경우에 구하기 어려운 단점이 존재한다. 그 외에 다른 기준으로 Spiegelhalter 등 (2002)가 제시한 DIC(Deviance Information Criterion)과 frequentist 추론에서의 P-value에 대비되는 Bayesian P-value가 있다. 본 논문에서는 Swiss banknote 자료를 Bayesian 로지스틱 회귀모형으로 분석하고 관련 기준들을 구하여 각 기준들이 일관성 있는 결론을 보이는지 확인하고자 한다.

그래프 LASSO에서 모형선택기준의 비교 (Comparison of model selection criteria in graphical LASSO)

  • 안형석;박창이
    • Journal of the Korean Data and Information Science Society
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    • 제25권4호
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    • pp.881-891
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    • 2014
  • 그래프모형(graphical model)은 확률 변수들간의 조건부 독립성(conditional independence)을 시각적인 네트워크형태로 표현할 수 있기 때문에, 정보학 (bioinformatics)이나 사회관계망 (social network) 등 수많은 변수들이 서로 연결되어 있는 복잡한 확률 시스템에 대한 직관적인 도구로 활용될 수 있다. 그래프 LASSO (graphical least absolute shrinkage and selection operator)는 고차원의 자료에 대한 가우스 그래프 모형 (Gaussian graphical model)의 추정에서 과대적합 (overfitting)을 방지하는데에 효과적인 것으로 알려진 방법이다. 본 논문에서는 그래프 LASSO 추정에서 매우 중요한 문제인 모형선택에 대하여 고려한다. 특히 여러가지 모형선택기준을 모의실험을 통해 비교하며 실제 금융 자료를 분석한다.

The Game Selection Model for the Payoff Strategy Optimization of Mobile CrowdSensing Task

  • Zhao, Guosheng;Liu, Dongmei;Wang, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권4호
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    • pp.1426-1447
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    • 2021
  • The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

정규분포기반 두각 혼합모형의 순환적 적합을 이용한 군집분석에서의 변수선택 (Variable Selection in Clustering by Recursive Fit of Normal Distribution-based Salient Mixture Model)

  • 김승구
    • 응용통계연구
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    • 제26권5호
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    • pp.821-834
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    • 2013
  • Law 등 (2004)은 군집분석에서 변수선택을 위해 정규분포기반 "두각 혼합모형(salient mixture model)"의 사용을 제안하였다. 본 논문에서는 이 모형의 적합 상의 문제점과 변수선택의 결함을 지적하고 그 대안을 제시한다. 모의자료와 실자료를 바탕으로 제안된 방법이 기존의 방법보다 유용함을 보였다.