• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.729-742
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• 2005

In this paper, we discuss the propriety of the various noninformative priors for the Pareto distribution. The reference prior, Jeffreys prior and ad hoc noninformative prior which is used in several literatures will be introduced and showed that which prior gives the proper posterior distribution. The reference prior and Jeffreys prior give a proper posterior distribution, but ad hoc noninformative prior which is proportional to reciprocal of the parameters does not give a proper posterior. To compute survival function, we use the well-known approximation method proposed by Lindley (1980) and Tireney and Kadane (1986). And two methods are compared by simulation. A real data example is given to illustrate our methodology.

• Journal of the Korean Data and Information Science Society
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• 제25권4호
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• pp.961-970
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• 2014

This article deals with the problem of testing the equality of the scale parameters of several inverted exponential distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters 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 default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1299-1308
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• 2012

This article deals with the problem of testing the equality of the scale parameters in nonregular Pareto distributions.We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be de ned up to a multiplicative constant. So we propose the default Bayesia hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.217-225
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• 2017

This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

• Journal of the Korean Data and Information Science Society
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• 제23권3호
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• pp.605-616
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• 2012

This article deals with the problem of testing on the common mean of several normal populations. We propose Bayesian hypothesis testing procedures for the common normal mean under the noninformative prior. The noninformative prior is usually improper and yields a calibration problem that makes the Bayes factor to be defined u to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1265-1273
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• 2011

This article deals with the problem of testing the equality of the location parameters in the half-normal distributions. We propose Bayesian hypothesis testing procedures for the equality of the location parameters under the noninformative prior. The non-informative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to arbitrary constants. This problem can be deal with the use of the fractional Bayes factor or intrinsic Bayes factor. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1569-1579
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• 2014

This article deals with the problem of testing for the equality of the shape parameters in two inverse Weibull distributions. We propose Bayesian hypothesis testing procedures for the equality of the shape parameters 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 default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2851-2865
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• 2014

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

• 대한전자공학회논문지SP
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• 제47권6호
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• pp.75-81
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• 2010

연골 영역화는 골관절염의 진단이나 치료를 위해 중요하지만, 모양이 얇고 의료영상 내에서 주변 조직과의 명암 차이가 크지 않기 때문에 현재까지 전문가가 많은 시간과 노력을 들여 수동으로 하고 있다. 이에 따라 본 논문에서는 3차원 자기공명(Magnetic Resonance : MR)영상 내에서 연골을 자동으로 영역화하는 기법을 제안한다. 제안하는 기법은 전문가에 의해 수동으로 영역화된 소수의 의료영상을 학습 데이터베이스로 하여 우선 연골을 지역적인 부분(local patch)들로 분할하여 부분별로 영역화한 후, 부분별 결과들을 취합하고 정제하는 과정으로 이루어진다. 연골 영역화를 위해 먼저 위치와 밝기 값의 외관정보 (appearance)를 이용하여 뼈와 연골의 경계(bone-cartilage interface)를 추출해내고, 이 경계를 기준으로 하여 연골이 포함되는 주변 영역을 일정한 크기의 패치로 분할한다. 다음, 분할된 패치들의 정보를 이용해, 패치마다 형상 사전지식(shape prior)과 외관 사전지식(appearance prior)을 얻어내고 두 사전지식 간의 비율을 적응적으로 결정한다. 이후 패치마다 사전지식 정보를 통해 에너지를 정의하고, 그래프 컷(Graph Cut) 기법을 통해 이 에너지를 최소화하는 최적의 영역화 결과를 도출한다. 마지막으로 지역적으로 얻어진 영역화 결과들을 모양 사전지식으로 하여 전체적인 연골에 대해 전역적 개선 과정을 수행한다. 실험 결과를 통해 제안하는 자동 영역화 기법으로 임상적으로 유용한 영역화 결과를 얻을 수 있음을 제시한다.