• 유통과학연구
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• 제18권7호
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• pp.19-25
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• 2020

Purpose: This study analyzes service quality of Pivate Brand (PB) productsto provide some academic and practical implications. Research design, data, and methodology: The focus is on how service quality of No Brand, which has recently received much attention, affects brand attitude and, to confirm whether consumers' prior knowledge of PB moderates this effect. A total of 167 men and women in their 20s who have experience using No Brand were surveyed. Hypothesis was verified by using hierarchical regression analysis. Results: a) Tangibles, reliability, empathy, and assurance of service quality for No Brand have a positive effect on brand attitude; b) The moderating effect of prior knowledge is only statistically significant in the context of reliability. Conclusion: This study provides academic and practical implications for establishing differentiated PB strategies. It highlights the effects of service quality and consumer prior knowledge on brand attitude. This suggests that the sub-dimension of PB service quality has a discriminatory effect on the brand attitude of No Brand, and that consumer's prior knowledge of the product influences reliability of service quality. Therefore, consumer's prior knowledge is important in order to increase trust.

• Advances in concrete construction
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• 제1권1호
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• pp.85-102
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• 2013

Prior concrete strength distributions can be updated by using direct information from test results as well as by taking into account indirect information due to conformity control. Due to the filtering effect of conformity control, the distribution of the material property in the accepted inspected lots will have lower fraction defectives in comparison to the distribution of the entire production (before or without inspection). A methodology is presented to quantify this influence in a Bayesian framework based on prior knowledge with respect to the hyperparameters of concrete strength distributions. An algorithm is presented in order to update prior distributions through numerical integration, taking into account the operating characteristic of the applied conformity criteria, calculated based on Monte Carlo simulations. Different examples are given to derive suitable hyperparameters for incoming strength distributions of concrete offered for conformity assessment, using updated available prior information, maximum-likelihood estimators or a bootstrap procedure. Furthermore, the updating procedure based on direct as well as indirect information obtained by conformity assessment is illustrated and used to quantify the filtering effect of conformity criteria on concrete strength distributions in case of a specific set of conformity criteria.

• 콘크리트학회지
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• 제11권2호
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• pp.241-249
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• 1999

실제 구조물의 정확하고 합리적인 압축강도 추정을 위해서는 통계학적으로 많은 실험데이타가 필요하다. 그러나, 실제로 압축강도 자료가 제한되어 있기 때문에 추정에 어려움이 있다. 따라서, 본 연구에서는 적은 자료를 가지고 콘크리트의 실제적인 압축강도 추정을 위해 합리적인 베이시안 기법을 도입하여 콘크리트 강도추정 방법을 제시하였다. 여기서, 콘크리트의 평균 압축강도는 확률변수로 고려한다. 콘크리트 압축강도의 베이시안 업데이팅을 위해 사전확률분포는 기존의 자료를 반영하여 표현하며, 우도함수는 측정치의 특성을 반영하였다. 사후확률분포는 사전확률분포와 우도함수를 조합하여 나타내었다. 콘크리트 교량 현장에서 제작한 실린더 공시체로부터 측정한 자료를 이용하여 수치해석을 수행하였다. 수치해석결과는 상대적으로 적은 개수의 측정자료를 사용하고도 실제에 가까운 사후확률분포를 추정할 수 있는 것을 보여 주고 있다. 또한, 우도함수 분포의 신뢰구간에 대한 사전확률분포의 신뢰구간의 상대적인 크기는 사후확률분포의 결정에 영향을 미치는 것으로 나타났다. 본 논문에서 제시된 방법은 적은 현장측정자료를 가지고도 합리적인 강도추정이 가능함을 보여주고 있으며, 실제에 유용하게 활용될 수 있을 것으로 사료된다.

• Communications for Statistical Applications and Methods
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• 제11권3호
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• pp.619-629
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• 2004

Binomial group testing or composite sampling is often used to estimate the proportion, p, of positive(infects, defectives) in a population when that proportion is known to be small; the potential benefits of group testing over one-at-a-time testing are well documented. The literature has focused on maximum likelihood estimation. We provide two Bayes estimators and compare them with the MLE. The first of our Bayes estimators uses an uninformative Uniform (0, 1) prior on p; the properties of this estimator are poor. Our second Bayes estimator uses a much more informative prior that recognizes and takes into account key aspects of the group testing context. This estimator compares very favorably with the MSE, having substantially lower mean squared errors in all of the wide range of cases we considered. The priors uses a Beta distribution, Beta ($\alpha$, $\beta$), and some advice is provided for choosing the parameter a and $\beta$ for that distribution.

• 산업경영시스템학회지
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• 제28권3호
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• pp.26-35
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• 2005

This paper is intended to compare the hazard rate estimations from Bayesian approach and maximum likelihood estimate(MLE) method. Hazard rate frequently involves unknown parameters and it is common that those parameters are estimated from observed data by using MLE method. Such estimated parameters are appropriate as long as there are sufficient data. Due to various reasons, however, we frequently cannot obtain sufficient data so that the result of MLE method may be unreliable. In order to resolve such a problem we need to rely on the judgement about the unknown parameters. We do this by adopting the Bayesian approach. The first one is to use a predictive distribution and the second one is a method called Bayesian estimate. In addition, in the Bayesian approach, the prior distribution has a critical effect on the result of analysis, so we introduce the method using computerized-simulation to elicit an effective prior distribution. For the simplicity, we use exponential and gamma distributions as a likelihood distribution and its natural conjugate prior distribution, respectively. Finally, numerical examples are given to illustrate the potential benefits of the Bayesian approach.

• Journal of the Korean Data and Information Science Society
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• 제26권3호
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• pp.763-772
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• 2015

In this paper, we develop the noninformative priors for the product of different powers of k means in the exponential distribution. We developed the first and second order matching priors. It turns out that the second order matching prior matches the alternative coverage probabilities, and is the highest posterior density matching prior. Also we revealed that the derived reference prior is the second order matching prior, and Jeffreys' prior and reference prior are the same. We showed that the proposed reference prior matches very well the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

• Journal of the Korean Data and Information Science Society
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• 제21권1호
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• pp.163-172
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• 2010

In this paper, we deal with the problem for testing homogeneity of coecients of variation in several normal distributions. We propose Bayesian hypothesis testing procedures based on the Bayes factor under noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. So we propose the objective Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 추계학술대회
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• pp.27-34
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• 2005

We consider the problem of estimating the system reliability noninformative priors when both stress and strength follow generalized gamma distributions. We first derive Jeffreys' prior, group ordering reference priors, and matching priors. We investigate the propriety of posterior distributions and provide marginal posterior distributions under those noninformative priors. We also examine whether the reference priors satisfy the probability matching criterion.

• 응용통계연구
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• 제7권2호
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• pp.263-268
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• 1994

베이스(Thomas Bayes)는 역사적인 1764년 논문에서 공 W의 위치 $\theta$에 대한 추론 문제를 생각한 바 있다. 이 때 그는 $\theta$에 대한 사전(prior) 분포로서 균일(uniform) 분포를 가정하였는데, 본 소고에서는 이 사전분포가 단순한 주관적 확률이 아닌 논리적 확률로 간주될 수 있음을 보일 것이다.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1379-1390
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• 2008

This article deals with the problem of testing the difference of quantiles in exponential distributions. We propose Bayesian hypothesis testing procedures for the difference of two quantiles under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the matching prior. Simulation study and a real data example are provided.