• Title/Summary/Keyword: Jeffrey's prior

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Jeffrey′s Noninformative Prior in Bayesian Conjoint Analysis

  • Oh, Man-Suk;Kim, Yura
    • Journal of the Korean Statistical Society
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    • v.29 no.2
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    • pp.137-153
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    • 2000
  • Conjoint analysis is a widely-used statistical technique for measuring relative importance that individual place on the product's attributes. Despsite its practical importance, the complexity of conjoint model makes it difficult to analyze. In this paper, w consider a Bayesian approach using Jeffrey's noninformative prior. We derive Jeffrey's prior and give a sufficient condition under which the posterior derived from the Jeffrey's prior is paper.

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Noninformative priors for the scale parameter in the generalized Pareto distribution

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1521-1529
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    • 2013
  • In this paper, we develop noninformative priors for the generalized Pareto distribution when the scale parameter is of interest. We developed the rst order and the second order matching priors. We revealed that the second order matching prior does not exist. It turns out that the reference prior and Jeffrey's prior do not satisfy a first order matching criterion, and Jeffreys' prior, the reference prior and the matching prior are different. Some simulation study is performed and a real example is given.

NONINFORMATIVE PRIORS FOR PARETO DISTRIBUTION : REGULAR CASE

  • Kim, Dal-Ho;Lee, Woo-Dong;Kang, Sang-Gil
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.05a
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    • pp.27-37
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    • 2003
  • In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jeffrey's prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. And a real example will be given.

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A Study on Noninformative Priors of Intraclass Correlation Coefficients in Familial Data

  • Jin, Bong-Soo;Kim, Byung-Hwee
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.395-411
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    • 2005
  • In this paper, we develop the Jeffreys' prior, reference prior and the the probability matching priors for the difference of intraclass correlation coefficients in familial data. e prove the sufficient condition for propriety of posterior distributions. Using marginal posterior distributions under those noninformative priors, we compare posterior quantiles and frequentist coverage probability.

Bayesian Analysis for Multiple Capture-Recapture Models using Reference Priors

  • Younshik;Pongsu
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.165-178
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    • 2000
  • Bayesian methods are considered for the multiple caputure-recapture data. Reference priors are developed for such model and sampling-based approach through Gibbs sampler is used for inference from posterior distributions. Furthermore approximate Bayes factors are obtained for model selection between trap and nontrap response models. Finally one methodology is implemented for a capture-recapture model in generated data and real data.

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Noninformative priors for the common shape parameter of 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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    • v.26 no.1
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    • pp.243-253
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    • 2015
  • In this paper, we develop the noninformative priors for the common shape parameter of several inverse Gaussian distributions. Specially, we want to develop noninformative priors which satisfy certain objective criterion. The probability matching priors and reference priors of the common shape parameter will be developed. It turns out that the second order matching prior does not exist. The reference priors satisfy the first order matching criterion, but Jeffrey's prior is not the first order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

Noninformative priors for the shape parameter in the generalized Pareto distribution

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.1
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    • pp.171-178
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    • 2013
  • In this paper, we develop noninformative priors for the generalized Pareto distribution when the parameter of interest is the shape parameter. We developed the first order and the second order matching priors.We revealed that the second order matching prior does not exist. It turns out that the reference prior satisfies a first order matching criterion, but Jeffrey's prior is not a first order matching prior. Some simulation study is performed and a real example is given.

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

  • Won, Dong-Yeon;Lim, Jun Hyoung;Sim, Hyun Su;Sung, Si-il;Lim, Heonsang;Kim, Yong Soo
    • Journal of Applied Reliability
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    • v.17 no.3
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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.

Noninformative Priors for the Ratio of Means of Two Poisson Distributions

  • Kang, Sang-Gil;Lee, Woo-Dong;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.201-207
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    • 2002
  • In this paper, Jeffrey's and reference priors are derived when the parameter of interest is the ratio of means of two in dependent Poisson distribution. To achieve the parameter orthogonality in the sense of Cox and Reid (1987), non-trivial orthogonal transformation is provided. The orthogonal transformation makes to find noninformative priors easy. Our simulation study indicates that the reference prior meet very well the target coverage probabilities in a frequentist sense. Using the real data, we compute Bayes estimator and MLE for the ratio of means based on the reference prior.

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Reducing frame rate and pulse rate for routine diagnostic cerebral angiography: ALARA principles in practice

  • Arvin R. Wali;Sarath Pathuri;Michael G. Brandel;Ryan W. Sindewald;Brian R. Hirshman;Javier A. Bravo;Jeffrey A. Steinberg;Scott E. Olson;Jeffrey S. Pannell;Alexander Khalessi;David Santiago-Dieppa
    • Journal of Cerebrovascular and Endovascular Neurosurgery
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    • v.26 no.1
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    • pp.46-50
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    • 2024
  • Objective: Diagnostic cerebral angiograms (DCAs) are widely used in neurosurgery due to their high sensitivity and specificity to diagnose and characterize pathology using ionizing radiation. Eliminating unnecessary radiation is critical to reduce risk to patients, providers, and health care staff. We investigated if reducing pulse and frame rates during routine DCAs would decrease radiation burden without compromising image quality. Methods: We performed a retrospective review of prospectively acquired data after implementing a quality improvement protocol in which pulse rate and frame rate were reduced from 15 p/s to 7.5 p/s and 7.5 f/s to 4.0 f/s respectively. Radiation doses and exposures were calculated. Two endovascular neurosurgeons reviewed randomly selected angiograms of both doses and blindly assessed their quality. Results: A total of 40 consecutive angiograms were retrospectively analyzed, 20 prior to the protocol change and 20 after. After the intervention, radiation dose, radiation per run, total exposure, and exposure per run were all significantly decreased even after adjustment for BMI (all p<0.05). On multivariable analysis, we identified a 46% decrease in total radiation dose and 39% decrease in exposure without compromising image quality or procedure time. Conclusions: We demonstrated that for routine DCAs, pulse rate of 7.5 with a frame rate of 4.0 is sufficient to obtain diagnostic information without compromising image quality or elongating procedure time. In the interest of patient, provider, and health care staff safety, we strongly encourage all interventionalists to be cognizant of radiation usage to avoid unnecessary radiation exposure and consequential health risks.