• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.297-308
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• 2010

This article deals with the problem of testing mean when the coefficient of variation in normal distribution is known. We propose Bayesian hypothesis testing procedures for the normal mean 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 reference prior. Specially, we develop intrinsic priors which give asymptotically same Bayes factor with the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.429-440
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• 2008

In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.315-323
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• 2011

This paper proposes two methods of estimating prior distribution to improve the performance of rapid speaker adaptation based on maximum a posteriori linear regression (MAPLR). In general, prior distribution of the transformation matrix used in MAPLR adaptation is estimated from all of the training speakers who are employed to construct the speaker-independent model, and it is applied identically to all new speakers. In this paper, we propose a method in which prior distribution is estimated from a group of reference speakers, selected using adaptation data, so that the acoustic characteristics of the selected reference speakers may be similar to that of the new speaker. Additionally, in MAPLR adaptation with block-diagonal transformation matrix, we propose a method in which the mean matrix and covariance matrix of prior distribution are estimated from two groups of transformation matrices obtained from the same training speakers, respectively. To evaluate the performance of the proposed methods, we examine word accuracy according to the number of adaptation words in the isolated word recognition task. Experimental results show that, for very limited adaptation data, statistically significant performance improvement is obtained in comparison with the conventional MAPLR adaptation.

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

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.523-532
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• 1999

Generalized linear models have various applications for data arising from many kinds of statistical studies. Although the response variable is generally assumed to be generated from a wide class of probability distributions we focus on count data that are most often analyzed using binomial models for proportions or poisson models for rates. The methods and results presented here also apply to many other categorical data models in general due to the relationship between multinomial and poisson sampling. The novelty of the approach suggested here is that all conditional distribution s can be specified directly so that staraightforward Gibbs sampling is possible. The prior distribution consists of two stages. We rely on a normal nonconjugate prior at the first stage and a vague prior for hyperparameters at the second stage. The methods are demonstrated with an illustrative example using data collected by Rosenkranz and raftery(1994) concerning the number of hospital admissions due to back pain in Washington state.

• Journal of Distribution Science
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• v.12 no.5
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• pp.15-26
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• 2014

Purpose - This study addresses an acquisition's impact on a firm's strategic relationship based on findings of existing academic studies and theoretical assertions. Through examining existing research results and theoretical grounds for an acquisition's impact on various stakeholders, this study indirectly approaches the impact on stakeholders including alliance partners. Research design, data, and methodology - This research identified a variety of related theoretical foundations and empirical studies. Research objectives of prior studies mainly focused on merging firms and direct participants of acquisition activity. In addition, academic attention on the impact on rival firms has recently been growing. However, little research on alliance partners was found. Prior studies simultaneously employed event study methodology and cross-sectional analysis to make further theoretical contributions. Results and Conclusions - Based on the findings of prior studies, this research proposed a complementary research model for future academic inquiry into the impact of an acquisition on an alliance partner's return and for predicting an acquisition announcement's effect on alliance partners.

• Journal of Korean Society for Quality Management
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• v.10 no.2
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• pp.25-33
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• 1982

We discuss a model for acceptance/rejection decision regarding finite populations. The model is based on a beta-binomial prior distribution and additive costs -- relative sampling costs, relative sorting costs and costs of accepted defectives. A substantial part of the paper is devoted to constructing a Bayes sequential sampling acceptance plan (BSSAP) for attributes under the model. It is shown that the Bayes fixed size sampling acceptance plans (BFSAP) are better than the Hald's (1960) single sampling acceptance plans based on a uniform prior. Some tables and examples are provided for comprisons of the minimum Bayes risks of the BSSAP and those of the BFSAP based on a uniform prior and the model.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.315-326
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• 2013

Despite of the importance on the maintenance of a reservoir storage, relatively few studies have addressed the stochastic reliability analysis including uncertainty on the decrease of the reservoir storage by the sedimentation. Therefore, the stochastic gamma process under the reliability framework is developed and applied to estimate the reduction of the Soyang Dam reservoir storage in this paper. Especially, in the estimation of parameters of the stochastic gamma process, the Bayesian MCMC scheme using informative prior distribution is used to incorporate a wide variety of information related with the sedimentation. The results show that the selected informative prior distribution is reasonable because the uncertainty of the posterior distribution is reduced considerably compared to that of the prior distribution. Also, the range of the expected life time of the dead storage in Soyang Dam reservoir including uncertainty is estimated from 119.3 years to 183.5 years at 5% significance level. Finally, it is suggested that the improvement of the assessment strategy in this study can provide the valuable information to the decision makers who are in charge of the maintenance of a reservoir.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.75-81
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• 2019

The paper aims to investigate the linkage among prior financial performance, organizational reputation and earnings quality. Firstly, it examines the influence of prior financial performance on organizational reputation and on earnings quality. Secondly, this research explores the moderating role that prior financial performance plays in the causal relationship from organizational reputation to earnings quality. Thirdly, the mediating role of organizational reputation in the effect of prior financial performance on earnings quality is analyzed. The empirical findings show that, prior financial performance positively affects both earnings quality and organizational reputation that in turn partly mediates the causal connection from prior financial performance to earnings quality; whereas prior financial performance imposes a positive moderation in the influence of organizational reputation on earnings quality. This research is expected to provide scholars and practitioners with a thorough understanding of the complex link among prior financial performance, organizational reputation and earnings quality. That helps them to deliver good decisions on the investment of suitable resources in maintaining and enhancing their organizational reputation, which assures a higher quality of reported earnings that in turn improves involved stakeholders' confidence in their firm. This likely leads the firms to gain better performance in the future.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.53-57
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• 1979

The concept of AOQL in designing Dodge's continuous sampling plans is modified to include probabilistic consideration reflecting the prior knowledge about the process average fraction defectives, and a new design criterion called AOQL, which eliminates some of the drawbacks of the AOQL criterion is proposed. AOQL, approach provides more economical sampling plans in many cases, and can be used even when only limited amount of prior information is available.