• Title/Summary/Keyword: bayesian

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A Bayesian Hypothesis Testing Procedure Possessing the Concept of Significance Level

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.787-795
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    • 2001
  • In this paper, Bayesian hypothesis testing procedures are proposed under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical ones in the sense of using the concept of significance level. The performances of proposed procedures are compared with those of classical procedures through several examples.

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A Bayesian approach to maintenance strategy for non-renewing free replacement-repair warranty

  • Jung, K.M.
    • International Journal of Reliability and Applications
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    • 제12권1호
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    • pp.41-48
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    • 2011
  • This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

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PERFORMANCE EVALUATION OF INFORMATION CRITERIA FOR THE NAIVE-BAYES MODEL IN THE CASE OF LATENT CLASS ANALYSIS: A MONTE CARLO STUDY

  • Dias, Jose G.
    • Journal of the Korean Statistical Society
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    • 제36권3호
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    • pp.435-445
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    • 2007
  • This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.

Bayesian Approach for Independence Test in Bivariate Exponential Model

  • 조장식
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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    • pp.327-333
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    • 2006
  • In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

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시변환 스트레스 조건에서의 와이블 분포의 모수 및 가속 모수에 대한 베이시안 추정을 사용하는 이산 시간 접근 방법 (A Discrete Time Approximation Method using Bayesian Inference of Parameters of Weibull Distribution and Acceleration Parameters with Time-Varying Stresses)

  • 정인승
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1331-1336
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    • 2008
  • This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

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A Bayesian Analysis of the Multinomial Randomized Response Model Using Dirichlet Prior Distribution

  • Kim, Jong-Min;Heo, Tae-Young
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 춘계 학술발표회 논문집
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    • pp.239-244
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    • 2005
  • In this paper, we examine the problem of estimating the sensitive characteristics and behaviors in a multinomial randomized response (RR) model. We analyze this problem through a Bayesian perspective and develop a Bayesian multinomial RR model in survey study. The Bayesian inference of multinomial RR model is a new approach to RR models.

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Bayesian Multiple Comparison of Binomial Populations based on Fractional Bayes Factor

  • Kim, Dal-Ho;Kang, Sang-Gil;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.233-244
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    • 2006
  • In this paper, we develop the Bayesian multiple comparisons procedure for the binomial distribution. We suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. An example is illustrated for the proposed method. For this example, the suggested method is straightforward for specifying distributionally and to implement computationally, with output readily adapted for required comparison. Also, some simulation was performed.

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Bayesian Method를 적용한 성능기반설계기법(PBD)의 활용 (Implementation of Performance Based Design Method based on Application of Bayesian Method)

  • 김장호;이경민;박정호;홍종석;이정
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2006년도 추계 학술발표회 논문집
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    • pp.217-220
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    • 2006
  • In this paper Satisfaction Curve has been applied to estimate the material safety by using Bayesian Method based on given parameters which are obtained from experimental results of other researchers. From the results, Bayesian Method is proven to be an available method for safety estimation of material.

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Bayesian Multiple Comparison of Bivariate Exponential Populations based on Fractional Bayes Factor

  • Cho, Jang-Sik;Cho, Kil-Ho;Choi, Seung-Bae
    • Journal of the Korean Data and Information Science Society
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    • 제17권3호
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    • pp.843-850
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    • 2006
  • In this paper, we consider the Bayesian multiple comparisons problem for K bivariate exponential populations to make inferences on the relationships among the parameters based on observations. And we suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Also, we give a numerical examples to illustrate our procedure.

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A Bayesian Approach to PM Model with Random Maintenance Quality

  • Jung, Ki-Mun
    • Journal of the Korean Data and Information Science Society
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    • 제18권3호
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    • pp.689-696
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    • 2007
  • This paper considers a Bayesian approach to determine an optimal PM policy with random maintenance quality. Thus, we assume that the quality of a PM action is a random variable following a probability distribution. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal PM policy. Finally, the numerical examples are presented for illustrative purpose.

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