• Title/Summary/Keyword: Probability of reference

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Reference Priors in a Two-Way Mixed-Effects Analysis of Variance Model

  • Chang, In-Hong;Kim, Byung-Hwee
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.317-328
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    • 2002
  • We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

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The Reference-Class Problem and the Qua-Problem (준거집합 문제와 자격의 문제)

  • Kim, Han-Seung
    • Korean Journal of Logic
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    • v.15 no.2
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    • pp.223-250
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    • 2012
  • The reference-class problem is known as a problem that frequentism on the nature of probability is supposed to encounter. Alan H$\acute{a}$jek argues that other theories on the nature of probability also meet this problem inevitably and claims that we can resolve the problem by regarding conditional probabilities as primitive. In this paper I shall present an adequate way of understanding the reference-class problem and its philosophical implications by scrutinizing his argument. H$\acute{a}$jek's claim is to be classified into the following two: (i) probability is relative to its reference class and (ii) what is known as the 'Ratio' analysis of conditional probability is wrong. H$\acute{a}$jek believes that these two are to be closely related but I believe these two should be separated. Moreover, I shall claim that we should accept the former but not the latter. Finally, regarding the identity condition of reference class I shall distinguish the extensional criterion from the non-extensional one. I shall claim that the non-extensional criterion is the right one for the identity condition of reference class by arguing that the reference-class problem should be regarded as an instance of the qua-problem.

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DEVELOPING NONINFORMATIVE PRIORS FOR THE FAMILIAL DATA

  • Heo, Jung-Eun;Kim, Yeong-Hwa
    • Journal of the Korean Statistical Society
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    • v.36 no.1
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    • pp.77-91
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    • 2007
  • This paper considers development of noninformative priors for the familial data when the families have equal number of offspring. Several noninformative priors including the widely used Jeffreys' prior as well as the different reference priors are derived. Also, a simultaneously-marginally-probability-matching prior is considered and probability matching priors are derived when the parameter of interest is inter- or intra-class correlation coefficient. The simulation study implemented by Gibbs sampler shows that two-group reference prior is slightly edge over the others in terms of coverage probability.

Developing Noninformative Priors for Parallel-Line Bioassay

  • Kim, YeongHwa;Heo, JungEun
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.401-410
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    • 2002
  • This paper revisits parallel-line bioassay problem, from a Bayesian point of view using noninformative priors such as Jeffreys' prior, reference priors, and probability matching priors. After finding the orthogonal transformation, the class of first order and second order probability matching priors are derived. Jeffreys' prior and reference priors are derived also. Numerical examples are given to show the effectiveness of noninformative priors.

Noninformative priors for Pareto distribution

  • Kim, Dal-Ho;Kang, Sang-Gil;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.6
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    • pp.1213-1223
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    • 2009
  • In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jereys' prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order matching prior and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. A real example is also considered.

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Effective Reference Probability Incorporating the Effect of Expiration Time in Web Cache (웹 캐쉬에서 만기시간의 영향을 고려한 유효참조확률)

  • Lee, Jeong-Joon;Moon, Yang-Se;Whang, Kyu-Young;Hong, Eui-Kyung
    • Journal of KIISE:Databases
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    • v.28 no.4
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    • pp.688-701
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    • 2001
  • Web caching has become an important problem addressing the performance issues in web applications. In this paper we propose a method that enhances the performance of web caching by incorporating the expiration time of web data we introduce the notion of the effective reference probability that incorporates the effect of expiration time into the reference probability used in the existing cache replacement algorithms .We formally define the effective reference probability and derive it theoretically using a probabilistic model. By simply replacing probabilities with the effective reference probability in the existing cache replacement algorithms we can take the effect of expiration time into account The results of performance evaluation through experiments show that the replacement algorithms using the effective reference probability always outperform the existing ones. The reason is that the proposed method precisely reflects the theoretical probability of getting the cache effect, and thus, incorporates the influence of the expiration time more effectively. In particular when the cache fraction is 0.05 and data update is comparatively frequent (i.e. the update frequency is more than 1/0 of the reference frequency) the performance enhancement is more than 30% in LRU-2 and 13% in Aggarwal's method (PSS integrating a refresh overhead factor) The results show that effective reference probability contributes significantly to the performance enhancement of the web cache in the presence of expiration time.

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Noninformative Priors for the Intraclass Coefficient of a Symmetric Normal Distribution

  • Chang, In-Hong;Kim, Byung-Hwee
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.15-19
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    • 2003
  • In this paper, we develop the Jeffreys' prior, reference priors and the probability matching priors for the intraclass correlation coefficient of a symmetric normal distribution. We next verify propriety of posterior distributions under those noninformative priors. We examine whether reference priors satisfy the probability matching criterion.

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Development of Noninformative Priors in the Burr Model

  • Cho, Jang-Sik;Kang, Sang-Gil;Baek, Sung-Uk
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.83-92
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    • 2003
  • In this paper, we derive noninformative priors for the ratio of parameters in the Burr model. We obtain Jeffreys' prior, reference prior and second order probability matching prior. Also we prove that the noninformative prior matches the alternative coverage probabilities and a HPD matching prior up to the second order, respectively. Finally, we provide simulated frequentist coverage probabilities under the derived noninformative priors for small and moderate size of samples.

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A Study on Noninformative Priors of Intraclass Correlation Coefficients in Familial Data

  • Jin, Bong-Soo;Kim, Byung-Hwee
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.395-411
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    • 2005
  • In this paper, we develop the Jeffreys' prior, reference prior and the the probability matching priors for the difference of intraclass correlation coefficients in familial data. e prove the sufficient condition for propriety of posterior distributions. Using marginal posterior distributions under those noninformative priors, we compare posterior quantiles and frequentist coverage probability.

Bayesian Inference for Stress-Strength Systems

  • Chang, In-Hong;Kim, Byung-Hwee
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.10a
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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.

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