• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1521-1529
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• v.12 no.2
• /
• pp.395-411
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.829-836
• /
• 2000

We shall derive Bayes estimators for he smaller and larger of two Pareto scale parameters with a common known shape parameter when the order of the scales is unknown and sample sizes are equal under squared error loss function. Also, we shall obtain biases and man squared errors for proposed Bayes estimators, and compare numerically performances for the proposed Bayes estimators.

• Journal of Radiation Protection and Research
• /
• v.30 no.2
• /
• pp.91-97
• /
• 2005

Bayesian methodology is appropriated for use in PRA because subjective knowledges as well as objective data are applied to assessment. In this study, radiological risk based on Bayesian methodology is assessed for the loss of source in field radiography. The exposure scenario for the lost source presented in U.S. NRC is reconstructed by considering the domestic situation and Bayes theorem is applied to updating of failure probabilities of safety functions. In case of updating of failure probabilities, it shows that 5 % Bayes credible intervals using Jeffreys prior distribution are lower than ones using vague prior distribution. It is noted that Jeffreys prior distribution is appropriated in risk assessment for systems having very low failure probabilities. And, it shows that the mean of the expected annual dose for the public based on Bayesian methodology is higher than the dose based on classical methodology because the means of the updated probabilities are higher than classical probabilities. The database for radiological risk assessment are sparse in domestic. It summarizes that Bayesian methodology can be applied as an useful alternative lot risk assessment and the study on risk assessment will be contributed to risk-informed regulation in the field of radiation safety.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.235-242
• /
• 2002

In this paper, we develop noninformative priors that are used for estimating the ratio of failure rates under Freund's bivariate exponential distribution. A class of priors is found by matching the coverage probabilities of one-sided Baysian credible interval with the corresponding frequentist coverage probabilities. Also the propriety of posterior under the noninformative priors is proved and the frequentist coverage probabilities are investigated for small samples via simulation study.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.1
• /
• pp.59-74
• /
• 2004

The paper considers the Bayesian interval estimation for the common mean of several normal populations. A Bayesian procedure is proposed based on the idea of matching asymptotically the coverage probabilities of Bayesian credible intervals with their frequentist counterparts. Several frequentist procedures based on pivots and P-values are introduced and compared with Bayesian procedure through simulation study. Both simulation results demonstrate that the Bayesian procedure performs as well or better than any available frequentist procedure even from a frequentist perspective.