• Educational Technology International
• /
• v.15 no.1
• /
• pp.1-26
• /
• 2014

The purpose of this study was to develop design principles of both animated pedagogical agents as 'credible' persuasive message source and persuasive fear arousing instructional messages in order to help enhance attitude changes toward a certain issue. Based on the previous pedagogical agent research, this study drew the design principles providing ways to manipulate agent credibility level and fear arousing level of message. Consequently, it specified how to make pedagogical agents perceived less or more credible by learners by manipulating a variety of agent features. For fear arousing message, this study showed how fear arousing messages would be structured into one of three levels: non-threatening, moderately threatening, and strongly threatening. Two different agent conditions and three message conditions were actually developed and experimentally tested with the participants of 40 undergraduate students. The results showed that the agent design principles specified from the previous research worked well enough to make a distinction between the more credible agent and the less credible agent. The overall results of this study may indicate that the design strategies for fear arousing message are retained on the premise of some future refinements.

• Communications for Statistical Applications and Methods
• /
• v.14 no.1
• /
• pp.11-21
• /
• 2007

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the difference between two normal means with unknown com-mon variance. We derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We illustrate our results using real data analysis as well as simulation study.

• Journal of the Korean Statistical Society
• /
• v.23 no.2
• /
• pp.445-461
• /
• 1994

This paper deals with the problem of obtaining some Bayes estimators and Bayesian credible regions of a reliability function for the Rayleigh distribution. Using several priors for a reliability function some Bayes estimators and Bayes credible sets are proposed and studied under squared error loss and Harris loss. Also the performances and behaviors of the proposed Bayes estimators are examined via Monte Carlo simulations and some numericla examples are given.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.4
• /
• pp.1365-1374
• /
• 2006

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the difference between two normal means with known variances. We derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We show the similarity between derived two-sample results and the results for the one-sample case in Bernardo(1999).

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.1
• /
• pp.219-228
• /
• 2007

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the ratio of two normal variances. Specifically we derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We illustrate our results using real data analysis and simulation study.

• Journal of the Korean Statistical Society
• /
• v.31 no.1
• /
• pp.17-31
• /
• 2002

This paper considers noninformative priors for the power law process under failure truncation. Jeffreys'priors as well as reference priors are found when one or both parameters are of interest. These priors are compared in the light of how accurately the coverage probabilities of Bayesian credible intervals match the corresponding frequentist coverage probabilities. It is found that the reference priors have a definite edge over Jeffreys'prior in this respect.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.743-752
• /
• 2004

In this paper, we develop the Bayesian model selection procedure using the reference prior for comparing two nested model such as the independent and intraclass models using the distance or divergence between the two as the basis of comparison. A suitable criterion for this is the power divergence measure as introduced by Cressie and Read(1984). Such a measure includes the Kullback -Liebler divergence measures and the Hellinger divergence measure as special cases. For this problem, the power divergence measure turns out to be a function solely of $\rho$, the intraclass correlation coefficient. Also, this function is convex, and the minimum is attained at $\rho=0$. We use reference prior for $\rho$. Due to the duality between hypothesis tests and set estimation, the hypothesis testing problem can also be solved by solving a corresponding set estimation problem. The present paper develops Bayesian method based on the Kullback-Liebler and Hellinger divergence measures, rejecting $H_0:\rho=0$ when the specified divergence measure exceeds some number d. This number d is so chosen that the resulting credible interval for the divergence measure has specified coverage probability $1-{\alpha}$. The length of such an interval is compared with the equal two-tailed credible interval and the HPD credible interval for $\rho$ with the same coverage probability which can also be inverted into acceptance regions of $H_0:\rho=0$. Example is considered where the HPD interval based on the one-at- a-time reference prior turns out to be the shortest credible interval having the same coverage probability.

• Journal of the Korean Society for information Management
• /
• v.27 no.2
• /
• pp.21-35
• /
• 2010

The popularity of question answering communities such as Yahoo! Answers and Naver Knowledge-iN and increasing doubts about the competence of lay information providers prompted this study to explore answerers' strategies to provide a credible answer in a question answering community. Forty-four active answerers in Yahoo! Answers were included in this study, and interviews were conducted through email, chat, and over the telephone. This study identified a set of information sources the answerers used, an array of important strategies to provide a credible answer, and their perception of self-claimed expertise. Implications of results were discussed in the context of user instruction.

• Communications for Statistical Applications and Methods
• /
• v.27 no.1
• /
• pp.47-64
• /
• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.478-481
• /
• 2002

In these days, Cost and Scheduling was managed effectively because of introduction of EVMS to construction project. However the EVMS is appropriate methods to advanced country, so it is difficult to apply into domestic construction project. in this paper weighted value n, m was used of compositive index(CI) to forecast Estimate At Completion (EAC) using statistical analysis in credible interval the objective of this paper is to verify compositive index(CI) and to forecast Estimate At Completion (EAC).