• Journal of the Korean Statistical Society
• /
• v.36 no.2
• /
• pp.321-333
• /
• 2007

In the proportional hazard model with the beta process prior, the posterior computation with the discrete approximation is considered. The time period of interest is partitioned by small intervals. On each partitioning interval, the likelihood is approximated by that of a binomial experiment and the beta process prior is by a beta distribution. Consequently, the posterior is approximated by that of many independent binomial model with beta priors. The analysis of the leukemia remission data is given as an example. It is illustrated that the length of the partitioning interval affects the posterior and one needs to be careful in choosing it.

• Communications for Statistical Applications and Methods
• /
• v.21 no.3
• /
• pp.261-274
• /
• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

• Journal of the Korean Statistical Society
• /
• v.30 no.3
• /
• pp.467-480
• /
• 2001

This paper considers the use of local $\phi$-divergence measures between posterior distributions under classes of perturbations in order to investigate the inherent robustness of certain classes. The smaller value of the limiting local $\phi$-divergence implies more robustness for the prior or the likelihood. We consider the cases when the likelihood comes form the class of weighted distribution. Two kinds of perturbations are considered for the local sensitivity analysis. In addition, some numerical examples are considered which provide measures of robustness.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.268-275
• /
• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• Journal of Technologic Dentistry
• /
• v.31 no.1
• /
• pp.7-15
• /
• 2009

Purpose: This study was to propose the clear understanding for stress distribution of supporting bone by use of staggered buccal offset tripodal placement of fixtures of posterior 3 crown implant partial dentures. We realized posterior 3 crown implant fixed partial dentures through finite element modeling and analysed stress effect of implant arrangement location to supporting bone under external load using finite element method. Method: To understand stress distribution of 3 crown implant fixed partial dentures which have 2 different arrangement by finite element analysis. In each model, for loading condition, we applied $45^{\circ}$ oblique load to occlusal surface of crown and applied 100 N for 3 crown individually(total 300 N) for imitating possible oral loading condition. at this time, we calculated Von Mises stress distribution in supporting bone through finite element method. Result: When apply $45^{\circ}$ oblique load to in-line arrangement model, maximum stress result for 100 N for each 3 crown 47.566MPa. In tripodal placement, result for 1mm buccal offset tripodal placement implant model was maximum distributed load 51.418MPa, so result was higher than in-line arrangement model. Conclusion: In stress distribution result by placement of implant fixture, the most effective structure was in-line arrangement. The tripodal placement does not effective for stress distribution, gap cause more damage to supporting bone.

• Communications for Statistical Applications and Methods
• /
• v.25 no.5
• /
• pp.471-488
• /
• 2018

In this paper, we propose extending proportional hazards frailty models to allow a discrete distribution for the frailty variable. Having zero frailty can be interpreted as being immune or cured. Thus, we develop a new survival model induced by discrete frailty with zero-inflated power series distribution, which can account for overdispersion. This proposal also allows for a realistic description of non-risk individuals, since individuals cured due to intrinsic factors (immunes) are modeled by a deterministic fraction of zero-risk while those cured due to an intervention are modeled by a random fraction. We put the proposed model in a Bayesian framework and use a Markov chain Monte Carlo algorithm for the computation of posterior distribution. A simulation study is conducted to assess the proposed model and the computation algorithm. We also discuss model selection based on pseudo-Bayes factors as well as developing case influence diagnostics for the joint posterior distribution through ${\psi}-divergence$ measures. The motivating cutaneous melanoma data is analyzed for illustration purposes.

• Bulletin of the Korean Chemical Society
• /
• v.35 no.3
• /
• pp.701-702
• /
• 2014

• The Korean Journal of Nuclear Medicine Technology
• /
• v.19 no.1
• /
• pp.67-71
• /
• 2015

Purpose At recently, we enter into the aging society and a age-related disease is increasing. Among that, prevalence of degenerative brain disease like Parkin's disease will be increased. So, many radiopharmaceuticals is developed to diagnosis early and to evaluate the performance of therapeutic drugs. Especially $^{18}F-DOPA$ which involved at dopamine synthesis and function of storage is widely used to the diagnosis of Parkinson's disease as well as brain tumors. in the study, we will evaluate the distribution pattern of $^{18}F-DOPA$ at the striatum by using dynamic study. Materials and Methods We used Biograph Truepoint(Siemens, Germany) as PET/CT scanner, injected a $^{18}F-DOPA$ ($600{\pm}30MBq$) to patient (4men, 6women. $67{\pm}11age$) who visited our hospital from June to September, started 95min dynamic study at same time. after finishing acquisition, we reconstructed PET data with 19 frame every 5 minutes, analysed a average counts at ROI's where set at both striatums, anterior putamen, posterior putamen Results Counts in the cerebellum as the background formed a plateau after 90 minutes from the highest out rapidly reduced to 15 minutes. Counts of anterior putamen and posterior gradually increased but formed a plateau after 60min. A count ratio of Striatum to cerebellum was continuously increased up to more than 95 minutes, A count ratios of an anterior putamen to posterior one formed a plateau after 85 minutes. Conclusion The dynamic acquisition can be possible to evaluate a distribution of the $^{18}F-DOPA$ in the striatum and the VOI analysis through a dynamic acquisition and a variety of patterns. Futhermore, to make a uniformed distribution and count ratio of striatum to cerebellum, a static acquisition will have to start 90minutes later after injection.

• Journal of applied mathematics & informatics
• /
• v.6 no.2
• /
• pp.589-598
• /
• 1999

Classification errors are included in sampling -with -re-placement model where items are sampled from a Bernoulli process. Bayesian imperfect inspection model is considered. In addition con-jugate prior and predctive densities for imperfect inspection model are obtained.

• Proceedings of the Korean Statistical Society Conference
• /
• 2003.10a
• /
• pp.15-19
• /
• 2003

In this paper, we develop the Jeffreys' prior, reference priors and the probability matching priors for the intraclass correlation coefficient of a symmetric normal distribution. We next verify propriety of posterior distributions under those noninformative priors. We examine whether reference priors satisfy the probability matching criterion.