• Title/Summary/Keyword: Common scale parameter

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Noninformative priors for the common scale parameter in Pareto distributions

  • Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.335-343
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    • 2010
  • In this paper, we develop the reference priors for the common scale parameter in the nonregular Pareto distributions with unequal shape paramters. We derive the reference priors as noninformative prior and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

Noninformative Priors for the Common Scale Parameter in the Inverse Gaussian Distributions

  • Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.981-992
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    • 2004
  • In this paper, we develop the noninformative priors for the common scale parameter in the inverse gaussian distributions. We developed the first and second order matching priors. Next we revealed that the second order matching prior satisfies a HPD matching criterion. Also we showed that the second order matching prior matches alternative coverage probabilities up to the second order. It turns out that the one-at-a-time reference prior satisfies a second order matching criterion. Some simulation study is performed.

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Likelihood Based Confidence Intervals for the Common Scale Parameter in the Inverse Gaussian Distributions

  • Lee, Woo-Dong;Cho, Kil-Ho;Cha, Young-Joon;Ko, Jung-Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.963-972
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    • 2006
  • This paper focuses on the likelihood based confidence intervals for two inverse gaussian distributions when the parameter of interest is common scale parameter. Confidence intervals based on signed loglikelihood ratio statistic and modified signed loglikelihood ratio statistics will be compared in small sample through an illustrative simulation study.

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Noninformative priors for common scale parameter in the regular Pareto distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Kim, Yong-Ku
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.2
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    • pp.353-363
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    • 2012
  • In this paper, we introduce the noninformative priors such as the matching priors and the reference priors for the common scale parameter in the Pareto distributions. It turns out that the posterior distribution under the reference priors is not proper, and Jeffreys' prior is not a matching prior. It is shown that the proposed first order prior matches the target coverage probabilities in a frequentist sense through simulation study.

Two Sample Tests in the Weibull Distribution

  • Park, Won-Joon
    • Journal of the Korean Statistical Society
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    • v.8 no.2
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    • pp.99-105
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    • 1979
  • In Thoman and Bain and Schafer and Sheffield, procedures for testing the equality of the scale parameters of two Weibull populations with a common shape parameter and procedures for selecting the Weibull population with the largest scale parameter are given. We give, in this paper, a modified procedure for the above testing and selection problems, which is more powerful than those previoulsy given.

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Noninformative priors for the common location parameter in half-normal distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.757-764
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    • 2010
  • In this paper, we develop the reference priors for the common location parameter in the half-normal distributions with unequal scale paramters. We derive the reference priors as noninformative prior and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

A Large-scale Structural Mixing Model applied to Blowout of Turbulent Nonpremixed Jet Flames in a Cross air-flow

  • Lee, Kee-Man;Shin, Hyun-Dong
    • 한국연소학회:학술대회논문집
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    • 1997.06a
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    • pp.163-173
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    • 1997
  • This article presents an application of a large-scale structural mixing model (Broadwell et al. 1984) to the blowout of turbulent reacting jets discharging perpendicularly into an unconfined cross air-flow. In an analysis of a common stability curve, a plausible explanation can be made that the phenomenon of blowout is related only to the mixing time scale of the two flows. The most notable observation is that the blowout distance is traced at fixed positions at all times according to the velocity ratio R. Measurements of the lower blowout limits in the liftable flame agree qualitatively with the blowout parameter ${\varepsilon}$, proposed by Broadwell et al. Good agreement between the results calculated by a modified blowout parameter ${\varepsilon}^'$ and experimental results confirms the important effect of a large-scale structure in specifying the stabilization feature of blowouts.

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A two-stage elimination type procedure for selecting the largest gamma scale parameter (감마분포 처리의 최대 척도모수 선택에 관한 제거형 이단 선택방법)

  • 김순기
    • The Korean Journal of Applied Statistics
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    • v.1 no.2
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    • pp.27-33
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    • 1987
  • Let $\Pi_i, \cdots, \Pi_k$ denote k gamma distributions with a common known shape parameter (degrees of freedom) r and scale parameters $\theta_1, \cdots, \theta_k$, respectively. Kim proposed an improved lower bound LB$(\delta^*)$, which concerns a two-stage elimimation type procedure for selecting the population associated with the largest scale parameter $max_{1\leqi\leqk} \theta_i$. The design constants (nr, mr, c) are given for k=4(1)10, $p^*=.95,.90 and \delta^*=1.75,2.0$. With these design constants, a comparison study was made with the procedure of Lee and Choi. As can be seen from the table, these are moderate amount of savings in the expected total sample size. Thus, together with the result in Lee and Choi, the two-stage procedure can perform much better than a single stage procedure.

A Large-scale Structural Mixing Model applied to Blowout of Turbulent Nonpremixed Jet Flames in a Cross Jet Flow (횡분류(流)(橫噴流)에서 난류 비예흔합 화염의 화염날림에 대한 거대 와(渦)구조 혼합 모텔 적용)

  • Lee, Kee-Man;Park, Jeong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.26 no.1
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    • pp.133-140
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    • 2002
  • This article presents an application of a large-scale structural mixing model(Broadwell et at. 1984) to the blowout of turbulent reacting cross flow jets. Experimental observations, therefore, aim to identify the existence of large-scale vortical structure exerting an important effect upon the flame stabilization. In the analysis of common stability curve, it is seen that the phenomenon of blowout are only related to the mixing time scale of the two flows. The most notable observation is that the blowout distance is traced at a fixed positions according to the velocity ratio at all times. Measurements of the lower blowout limits in the liftable flame are qualitatively in agreement with the blowout parameter $\xi$, proposed by Broadwell et al. Good agrement between the results calculated by a modified blowout parameter $\xi$'and the present experimental results confirms the important effect of large-scale structure in the stabilization feature of blowout.

Noninformative priors for the common location parameter in half-t distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.6
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    • pp.1327-1335
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    • 2010
  • In this paper, we want to develop objective priors for the common location parameter in two half-t distributions with unequal scale parameters. The half-t distribution is a non-regular class of distribution. One can not develop the reference prior by using the algorithm of Berger of Bernardo (1989). Specially, we derive the reference priors and prove the propriety of joint posterior distribution under the developed priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.