• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.661-671
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• 2003

The Bayes factors with improper noninformative priors are defined only up to arbitrary constants. So, it is known that Bayes factors are not well defined due to this arbitrariness in Bayesian hypothesis testing and model selections. The intrinsic Bayes factor by Berger and Pericchi (1996) and the fractional Bayes factor by O'Hagan (1995) have been used to overcome this problems. This paper suggests intrinsic priors for testing the equality of two lognormal means, whose Bayes factors are asymptotically equivalent to the corresponding fractional Bayes factors. Using proposed intrinsic priors, we demonstrate our results with real example and a simulated dataset.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.927-932
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• 2006

The techniques for selecting and evaluating prior distributions are studied over recent years which the primary emphasis is on noninformative priors. But, noninformative priors are typically improper so that such priors are defined only up to arbitrary constants which affect the values of Bayes factors. In this paper, we consider the Bayesian hypotheses testing for the Weibull shape parameter based on fractional Bayes factor which is to remove the arbitrariness of improper priors. Also we present a numerical example to further illustrate our results.

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.429-440
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• 2008

In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian 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 the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.647-655
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• 2006

In this paper, we consider multiple comparisons for the ratio of the failure rates in two components system that the lifetimes of the components have independent exponential distributions. Also we suggest Bayesian multiple comparisons procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Finally, we give numerical examples to illustrate our procedure.

• Journal of the Korean Data and Information Science Society
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• 제20권6호
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• pp.1213-1223
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• 2009

In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jereys' prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order matching prior and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. A real example is also considered.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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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.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.1033-1043
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• 2004

We consider the simultaneous Bayesian estimation for the normal means based on different noninformative type hyperpriors in hierarchical model. We provide numerical example using the famous baseball data in Efron and Morris (1975) for illustration.

• 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.

• 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.

• Journal of the Korean Data and Information Science Society
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• 제22권2호
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• pp.361-369
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• 2011

In this paper, we develop the reference and the matching priors for the reliability function of two-parameter exponential distribution. We derive the reference priors and the matching prior, and prove the propriety of joint posterior distribution under the general prior including the reference priors and the matching prior. Through the sim-ulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.