• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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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.

• International Journal of Reliability and Applications
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• v.2 no.2
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• pp.117-130
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• 2001

Consider the problem of estimating the system reliability using noninformative priors when both stress and strength follow generalized gamma distributions. We first treat the orthogonal reparametrization and then, using this reparametrization, derive Jeffreys'prior, reference prior, and matching priors. We next provide the suffcient condition for propriety of posterior distributions under those noninformative priors. Finally, we provide and compare estimated values of the system reliability based on the simulated values of the parameter of interest in some special cases.

• Journal of Applied Reliability
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• v.3 no.2
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• pp.117-125
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• 2003

In sampling survey, prior-information about population has been generally ignored to estimate parameters. But if there is some believable prior-information about population, it is very useful to get more efficiency estimators by using the prior-information. This paper shows how to estimate the parameter, to evaluate the variance of the estimator, and to un-biasness of the estimator by using multiple stratification with prior-information about survey population. The proposed method is illustrated with a set of hypothetical data. The results show that the proposed estimator is very efficiency and strongly recommendable.

• Journal of the Korean Home Economics Association
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• v.40 no.5
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• pp.39-51
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• 2002

The purpose of this study is to investigate prior thinking and posterior thinking formation of children and adolescents in sinking objects. The subjects consisted of twenty eight, 9- and 11-year old children and fourteen, 13-year old adolescents selected from one elementary school and two middle schools. The transcripts were analyzed to classify children and adolescents'prior thinking and posterior thinking frequency, reasoning response(evidence based response, idea based response) and reasoning method(valid method, invalid method). The data were analyzed by frequency, percentile, mean and standard deviation,1 test, ANOVA. Major findings were as followings: 1. Children and adolescents have already had prior thinking in sinking objects. 2. Children and adolescents applies their prior thinking to posterior thinking formation process. 3. There were significant differences in children and adolescent'posterior thinking formation process, especially choices in objects and reasoning methods depending on age. 4. There were significant differences in children and adolescents'reasoning response depending on presented evidences types.5. Through the experimentation, children and adolescents'prior thinking was different from their posterior thinking. There were significant differences in differences between the prior thinking and posterior thinking depending on age.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3225-3234
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• 2022

Alloy 690 tubing has been shown to be highly resistant to primary water stress corrosion cracking (PWSCC). Nevertheless, predicting the failure by PWSCC in Alloy 690 SG tubes is indispensable. In this work, a Bayesian-based statistical approach is proposed to predict the occurrence of failure by PWSCC in Alloy 690 SG tubing. The prior distributions of the model parameters are developed based on the prior knowledge or information regarding the parameters. Since Alloy 690 is a replacement for Alloy 600, the parameter distributions of Alloy 600 tubing are used to gain prior information about the parameters of Alloy 690 tubing. In addition to estimating the model parameters, analysis of tubing reliability is also performed. Since no PWSCC has been observed in Alloy 690 tubing, only right-censored free-failure life of the tubing are available. Apparently the inference is sensitive to the choice of prior distribution when only right-censored data exist. Thus, one must be careful in choosing the prior distributions for the model parameters. It is found that the use of non-informative prior distribution yields unsatisfactory results, and strongly informative prior distribution will greatly influence the inference, especially when it is considerably optimistic relative to the observed data.

• Korean Association of Arts Management
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• no.54
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• pp.59-93
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• 2020

The development of digital technology has made consumers more knowledgeable about products than ever before. In this regard, experts have defined consumers in the digital age as knowledge seekers and pointed out that they are proficient in acquiring and sharing product knowledge prior to purchase. For service goods such as musicals, product prior knowledge executes strong effect due to such characteristics as intangibility, inseparabilit y,and heterogeneity. Prior studies in the field of performing arts, including musicals, have revealed that the prior knowledge of the audience has a positive effect on the satisfaction of the audience and WOM(word-of-mouth) intention. However, studies in the marketing field argue that consumers' high prior knowledge may have a negative impact on customer satisfaction and product evaluation depending on conditions, as they are more likely to compare, review, and expect products more closely. Therefore, in this study, we tried to identify under what conditions the musical prior knowledge enhances audience satisfaction and WOM intention. According to the results of previous studies, a mediating effect model was established in which the musical prior knowledge enhances the WOM intention through the mediation of the audience satisfaction. Then, Transportation was introduced as a mediation variable and it was verified whether the level changed the audience satisfaction and WOM intention. The reason for the introduction of the transportation construct reflects the results of previous research that the story is important component of musical. The results showed that the musical prior knowledge has a significant effect on WOM intention through the mediation of audience satisfaction. The moderating effect of transport was also significant on the relationship between musical prior knowledge and audience satisfaction. Lastly, through moderated-mediation analysis, it was confirmed that transportation moderates the mediating effect that prior knowledge affects on the WOM intention through audience satisfaction. Based on the results, we demonstrated that a musical story is fairly important to satisfy audiences with high prior knowledge. This study could contribute to the related filed in that it introduced the transportation construct for the first time, thereby broadening the understanding of the musical audiences in the era of smart consumers.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.249-257
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• 2017

This paper proposes a method to segment urban scenes semantically based on location prior information. Since major scene elements in urban environments such as roads, buildings, and vehicles are often located at specific locations, using the location prior information of these elements can improve the segmentation performance. The location priors are defined in special 2D coordinates, referred to as road-normal coordinates, which are perpendicular to the orientation of the road. With the help of depth information to each element, all the possible pixels in the image are projected into these coordinates and the learned prior information is applied to those pixels. The proposed location prior can be modeled by defining a unary potential of a conditional random field (CRF) as a sum of two sub-potentials: an appearance feature-based potential and a location potential. The proposed method was validated using publicly available KITTI dataset, which has urban images and corresponding 3D depth measurements.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.217-226
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• 2002

In this paper, we derive noninformative priors for the ratio of failure rates in exponential model. A class of priors is found by matching the coverage probabilities of one-sided Baysian credible interval with the corresponding frequentist coverage probabilities. And we prove that the noninformative prior matches the alternative coverage probabilities and is a HPD matching prior up to the second order. Finally, we provide simulated freqentist coverage probabilities under the derived noninformative prior for small samples.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.225-244
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• 2014

In this work, we discuss segmentation algorithms based on the level set method that incorporates shape prior knowledge. Fundamental segmentation models fail to segment desirable objects from a background when the objects are occluded by others or missing parts of their whole. To overcome these difficulties, we incorporate shape prior knowledge into a new segmentation energy that, uses global and local image information to construct the energy functional. This method improves upon other methods found in the literature and segments images with intensity inhomogeneity, even when images have missing or misleading information due to occlusions, noise, or low-contrast. We consider the case when the shape prior is placed exactly at the locations of the desired objects and the case when the shape prior is placed at arbitrary locations. We test our methods on various images and compare them to other existing methods. Experimental results show that our methods are not only accurate and computationally efficient, but faster than existing methods as well.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.719-729
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• 2003

We propose a Bayesian model selection procedure for nonlinear regression models under noninformative prior. For informative prior, Na and Kim (2002) suggested the Bayesian model selection procedure through MCMC techniques. We extend this method to the case of noninformative prior. The difficulty with the use of noninformative prior is that it is typically improper and hence is defined only up to arbitrary constant. The methods, such as Intrinsic Bayes Factor(IBF) and Fractional Bayes Factor(FBF), are used as a resolution to the problem. We showed the detailed model selection procedure through the specific real data set.