• 제목/요약/키워드: Prior Distributions

검색결과 207건 처리시간 0.023초

도시소각로에서 Polychlorinated-dibenzofurans (PCDFs)의 생성 예측 (Prediction of Polychlorinated-dibenzofurans (PCDFs) Formation in Municipal Waste Incinerator)

  • 류재용;서정민
    • 한국대기환경학회지
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    • 제22권6호
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    • pp.842-850
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    • 2006
  • The role of chlorination reactions in the formation of polychlorinated dibenzofurans (PCDFs) in a municipal waste incinerator was assessed using a chlorination model for predicting PCDF isomer distributions. Complete distributions of PCDF congeners were obtained from a stoker-type municipal waste incinerator operated under 13 test conditions. Samples were collected from the flue gas prior to the gas cleaning system. While total PCDF yields varied by a factor of five to six, the distributions of congeners were similar. A chlorination model, dependent only on the observed distribution of monochlorinated isomers, was developed to predict the distributions of poly-chlorinated isomers formed by chlorination of dibenzofuran (DF). Agreement between predicted and measured PCDF isomer distributions was high for all homologues, supporting the hypothesis that DF chlorination can play an important role in the formation of PCDF byproducts.

Default Bayesian testing equality of scale parameters in several inverse Gaussian distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • 제26권3호
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    • pp.739-748
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    • 2015
  • This paper deals with the problem of testing about the equality of the scale parameters in several inverse Gaussian distributions. We propose default Bayesian testing procedures for the equality of the shape parameters under the reference priors. The reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Therefore we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Default Bayesian hypothesis testing for the scale parameters in the half logistic distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • 제25권2호
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    • pp.465-472
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    • 2014
  • This article deals with the problem of testing the equality of the scale parameters in the half logistic distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. Thus we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Default Bayesian testing for scale parameters in the log-logistic distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1501-1511
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    • 2015
  • This paper deals with the problem of testing on the equality of the scale parameters in the log-logistic distributions. We propose default Bayesian testing procedures for the scale parameters under the reference priors. The reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Therefore, we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference priors. To justify proposed procedures, a simulation study is provided and also, an example is given.

Default Bayesian testing for the scale parameters in two parameter exponential distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • 제24권4호
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    • pp.949-957
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    • 2013
  • In this paper, we consider the problem of testing the equality of the scale parameters in two parameter exponential distributions. We propose Bayesian testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Thus, we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

MODIFIED GEOMETRIC DISTRIBUTION OF ORDER k AND ITS APPLICATIONS

  • JUNGTAEK OH;KYEONG EUN LEE
    • Journal of applied mathematics & informatics
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    • 제42권3호
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    • pp.709-723
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    • 2024
  • We study the distributions of waiting times in variations of the geometric distribution of order k. Variation imposes length on the runs of successes and failures. We study two types of waiting time random variables. First, we consider the waiting time for a run of k consecutive successes the first time no sequence of consecutive k failures occurs prior, denoted by T(k). Next, we consider the waiting time for a run of k consecutive failures the first time no sequence of k consecutive successes occurred prior, denoted by J(k). In addition, we study the distribution of the weighted average. The exact formulae of the probability mass function, mean, and variance of distributions are also obtained.

Noninformative Priors for the Difference of Two Quantiles in Exponential Models

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.431-442
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    • 2007
  • In this paper, we develop the noninformative priors when the parameter of interest is the difference between quantiles of two exponential distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that Jeffreys' prior does not satisfy the first order matching criterion. The Bayesian credible intervals based on the first order probability matching prior meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior. Some simulation and real example will be given.

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.

Bayesian Tomographic 재구성에 있어서 Gibbs Smoothing Priors의 효과에 대한 비교연구 (A Comparative Study of the Effects of Gibbs Smoothing Priors in Bayesian Tomographic Reconstruction)

  • 이수진
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 춘계학술대회
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    • pp.279-282
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    • 1997
  • Bayesian reconstruction methods for emission computed tomography have been a topic of interest in recent years, partly because they allow for the introduction of prior information into the reconstruction problem. Early formulations incorporated priors that imposed simple spatial smoothness constraints on the underlying object using Gibbs priors in the form of four-nearest or eight-nearest neighbors. While these types of priors, known as "membrane" priors, are useful as stabilizers in otherwise unstable ML-EM reconstructions, more sophisticated prior models are needed to model underlying source distributions more accurately. In this work, we investigate whether the "thin plate" model has advantages over the simple Gibbs smoothing priors mentioned above. To test and compare quantitative performance of the reconstruction algorithms, we use Monte Carlo noise trials and calculate bias and variance images of reconstruction estimates. The conclusion is that the thin plate prior outperforms the membrane prior in terms of bias and variance.

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베이지안 기법에 기반한 수명자료 분석에 관한 문헌 연구: 2000~2016 (A Review on the Analysis of Life Data Based on Bayesian Method: 2000~2016)

  • 원동연;임준형;심현수;성시일;임헌상;김용수
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권3호
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    • pp.213-223
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    • 2017
  • Purpose: The purpose of this study is to arrange the life data analysis literatures based on the Bayesian method quantitatively and provide it as tables. Methods: The Bayesian method produces a more accurate estimates of other traditional methods in a small sample size, and it requires specific algorithm and prior information. Based on these three characteristics of the Bayesian method, the criteria for classifying the literature were taken into account. Results: In many studies, there are comparisons of estimation methods for the Bayesian method and maximum likelihood estimation (MLE), and sample size was greater than 10 and not more than 25. In probability distributions, a variety of distributions were found in addition to the distributions of Weibull commonly used in life data analysis, and MCMC and Lindley's Approximation were used evenly. Finally, Gamma, Uniform, Jeffrey and extension of Jeffrey distributions were evenly used as prior information. Conclusion: To verify the characteristics of the Bayesian method which are more superior to other methods in a smaller sample size, studies in less than 10 samples should be carried out. Also, comparative study is required by various distributions, thereby providing guidelines necessary.