• 제목/요약/키워드: Bayes Factor

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Bayesian Hypothesis Testing for Intraclass Correlation Coefficient

  • Lee, Seung-A;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • 제13권3호
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    • pp.551-566
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    • 2006
  • In this paper, we consider a Bayesian model selection for the intraclass correlation coefficient in familiar data. In particular, we compare two nested models such as the independence and intraclass models using the reference prior. A criterion for testing is the Bayesian Reference Criterion by Bernardo (1999) and the Intrinsic Bayes Factor by Berger and Pericchi (1996). We provide numerical examples using simulation data sets for illustration.

Bayesian Model Selection in Analysis of Reciprocals

  • Kang, Sang-Gil;Kim, Dal-Ho
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2005년도 추계학술대회
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    • pp.85-93
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    • 2005
  • Tweedie (1957a) proposed a method for the analysis of residuals from an inverse Gaussian population paralleling the analysis of variance in normal theory. He called it the analysis of reciprocals. In this paper, we propose a Bayesian model selection procedure based on the fractional Bayes factor for the analysis of reciprocals. Using the proposed model procedures, we compare with the classical tests.

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Bayesian Test for Equality of Coefficients of Variation in the Normal Distributions

  • Lee, Hee-Choon;Kang, Sang-Gil;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.1023-1030
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    • 2003
  • When X and Y have independent normal distributions, we develop a Bayesian testing procedure for the equality of two coefficients of variation. Under the reference prior of the coefficient of variation, we propose a Bayesian test procedure for the equality of two coefficients of variation using fractional Bayes factor. A real data example is provided.

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Bayesian Model Selection in Analysis of Reciprocals

  • Kang, Sang-Gil;Kim, Dal-Ho;Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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    • pp.1167-1176
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    • 2005
  • Tweedie (1957a) proposed a method for the analysis of residuals from an inverse Gaussian population paralleling the analysis of variance in normal theory. He called it the analysis of reciprocals. In this paper, we propose a Bayesian model selection procedure based on the fractional Bayes factor for the analysis of reciprocals. Using the proposed model selection procedures, we compare with the classical tests.

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Bayesian Approach for Independence Test in Bivariate Exponential Model

  • 조장식
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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    • pp.327-333
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    • 2006
  • In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

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Bayesian Test for the Intraclass Correlation Coefficient in the One-Way Random Effect Model

  • Kang, Sang-Gil;Lee, Hee-Choon
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.645-654
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    • 2004
  • In this paper, we develop the Bayesian test procedure for the intraclass correlation coefficient in the unbalanced one-way random effect model based on the reference priors. That is, the objective is to compare two nested model such as the independent and intraclass models using the factional Bayes factor. Thus the model comparison problem in this case amounts to testing the hypotheses $H_1:\rho=0$ versus $H_2:{\rho}{\neq}0$. Some real data examples are provided.

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Bayesian Tests for Independence and Symmetry in Freund's Bivariate Exponential Model

  • Cho, Jang-Sik;Kim, Dal-Ho;Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.135-146
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    • 1999
  • In this paper, we consider the Bayesian hypotheses testing for independence and symmetry in Freund's bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. Also we derive the arithmetic and median intrinsic Bayes factors and use these results to analyze some data sets.

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Bayesian Multiple Comparison of Normal Populations based on Bayes Factor

  • Kang, Sang-Gil;Lee, Chang-Soon
    • 한국산업정보학회논문지
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    • 제7권1호
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    • pp.42-49
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    • 2002
  • 이 논문에서는 정규분포를 하는 모집단에 대한 베이지안 다중비교를 개발한다. 베이지안 다중비교를 위해서는 베이즈요인의 계산이 필수적인데 베이즈 요인의 계산은 O'Hagan (1995)이 제안한 부분베이즈 요인을 이용한다. 그리고 베이지안에서 필수적인 모수에 대한 사전분포로는 무정보적 사전분포를 이용한다. 또한, 비교대상이 되는 모집단의 수가 3이상인 경우에 대하여 베이즈요인의 정확한 형태를 유도했으며 정규분포를 한다고 널리 알려져 있는 자료를 제안된 방법으로 분석하는 사례를 보였으며, 모의실험을 통하여 제안된 방법의 유용성을 보였다.

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원초적 확률주의와 베이즈 인수 (Radical Probabilism and Bayes Factors)

  • 박일호
    • 논리연구
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    • 제11권2호
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    • pp.93-125
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    • 2008
  • 원초적 확률주의자들은 명제가 경험을 표상한다는 것을 거부한다. 그러나 경험의 영향은 다른 믿음에 전파되고, 다른 사람과 소통될 수 있어야 하기 때문에 명제와 다른 방식으로 경험, 혹은 경험의 영향을 표상할 수 있는 대안을 찾아야 한다. 그들이 제안하는 경험의 영향을 표상하는 유력한 대안은 베이즈 인수이다. 왜냐하면 베이즈 인수는 사전확률의 영향을 제외하고 있으며, 교환성 역시 성립하기 때문이다. 본 논문은 베이즈 인수만이 그런 역할을 하는 것이 아니라고 주장한다. 즉 베이즈 인수의 대안으로 제시된 q(E|$N_p$) 역시 사전확률의 영향이 제외되어 있으며, 교환성 또한 성립한다는 것을 보인다. 그리고 더 나아가 q(E|$N_p$)는 베이즈 인수가 결여한 프래그마틱한 장점을 가진다고 주장한다.

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Bayes estimation of entropy of exponential distribution based on multiply Type II censored competing risks data

  • Lee, Kyeongjun;Cho, Youngseuk
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1573-1582
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    • 2015
  • In lifetime data analysis, it is generally known that the lifetimes of test items may not be recorded exactly. There are also situations wherein the withdrawal of items prior to failure is prearranged in order to decrease the time or cost associated with experience. Moreover, it is generally known that more than one cause or risk factor may be present at the same time. Therefore, analysis of censored competing risks data are needed. In this article, we derive the Bayes estimators for the entropy function under the exponential distribution with an unknown scale parameter based on multiply Type II censored competing risks data. The Bayes estimators of entropy function for the exponential distribution with multiply Type II censored competing risks data under the squared error loss function (SELF), precautionary loss function (PLF) and DeGroot loss function (DLF) are provided. Lindley's approximate method is used to compute these estimators.We compare the proposed Bayes estimators in the sense of the mean squared error (MSE) for various multiply Type II censored competing risks data. Finally, a real data set has been analyzed for illustrative purposes.