• Title/Summary/Keyword: data distributions

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Experimental and numerical studies of mono-strand anchorage

  • Marceau, D.;Bastien, J.;Fafard, M.;Chabert, A.
    • Structural Engineering and Mechanics
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    • v.12 no.2
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    • pp.119-134
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    • 2001
  • This paper deals with an experimental and numerical study of a mono-strand wedge anchor head mechanism. First, the experimental program is presented and monitored data such as wedge slippage, anchor deflection and strain distributions along external peripheral surfaces of the anchor head are presented and discussed. In accordance with the experimental set up, these data concern only the global behaviour of the mechanism and cannot provide valuable information such as internal stress-strains distributions, stress concentrations and percentage of yielded volume. Therefore, the second part of this paper deals with the development of an efficient numerical finite element model capable of providing mechanism of the core information. The numerical model which includes all kinematics/material/contact non-linearities is first calibrated using experimental data. Subsequently, a numerical study of the anchorage mechanism is performed and its behaviour is compared to the behaviour of a slightly geometrically modified mechanism where the external diameter has been increased by 5 mm. Finally, different topics influencing the anchorage mechanism behaviour are addressed such as lubrication and wedge shape.

Noninformative priors for stress-strength reliability in the Pareto distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.1
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    • pp.115-123
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    • 2011
  • In this paper, we develop the noninformative priors for stress-strength reliability from the Pareto distributions. We develop the matching priors and the reference priors. It turns out that the second order matching prior does not match the alternative coverage probabilities, and is not a highest posterior density matching or a cumelative distribution function matching priors. Also we reveal that the one-at-a-time reference prior and Jeffreys' prior are the second order matching prior. We show that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example is given.

Assessment of Acoustic Iterative Inverse Method for Bubble Sizing to Experimental Data

  • Choi, Bok-Kyoung;Kim, Bong-Chae;Kim, Byoung-Nam;Yoon, Suk-Wang
    • Ocean Science Journal
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    • v.41 no.4
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    • pp.195-199
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    • 2006
  • Comparative study was carried out for an acoustic iterative inverse method to estimate bubble size distributions in water. Conventional bubble sizing methods consider only sound attenuation for sizing. Choi and Yoon [IEEE, 26(1), 125-130 (2001)] reported an acoustic iterative inverse method, which extracts the sound speed component from the measured sound attenuation. It can more accurately estimate the bubble size distributions in water than do the conventional methods. The estimation results of acoustic iterative inverse method were compared with other experimental data. The experimental data show good agreement with the estimation from the acoustic iterative inverse method. This iterative technique can be utilized for bubble sizing in the ocean.

Nonparametric test for unknown age class of life distributions

  • Abu-Youssef, S.E.;Mohammed, B.I.;Bakr, M.E.
    • International Journal of Reliability and Applications
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    • v.15 no.2
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    • pp.99-110
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    • 2014
  • Based on the kernel function, a new test is presented, testing $H_0:\bar{F}$ is exponential against $H_1:\bar{F}$ is UBACT and not exponential is given in section 2. Monte Carlos null distribution critical points for sample sizes n = 5(5)100 is investigated in section 3. The Pitman asymptotic efficiency for common alternatives is obtained in section 4. In section 5 we propose a test statistic for censored data. Finally, a numerical examples in medical science for complete and censored data using real data is presented in section 6.

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Default Bayesian testing for the equality of the scale parameters of several inverted exponential distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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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.

Bayesian testing for the homogeneity of the shape parameters of several inverse Gaussian distributions

  • Lee, Woo Dong;Kim, Dal Ho;Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.3
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    • pp.835-844
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    • 2016
  • We develop the testing procedures about the homogeneity of the shape parameters of several inverse Gaussian distributions in our paper. We propose default Bayesian testing procedures for the shape parameters under the reference priors. The Bayes factor based on the proper priors gives the successful results for Bayesian hypothesis testing. For the case of the lack of information, the noninformative priors such as Jereys' prior or the reference prior can be used. Jereys' prior or the reference prior involves the undefined constants in the computation of the Bayes factors. Therefore under the reference priors, we develop the Bayesian testing procedures with the intrinsic Bayes factors and the fractional Bayes factor. Simulation study for the performance of the developed testing procedures is given, and an example for illustration is given.

Default Bayesian hypothesis testing for the scale parameters in the half logistic distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.465-472
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    • 2014
  • This article deals with the problem of testing the equality of the scale parameters in the half logistic distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. Thus 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.

Estimation of Design Flood by the Determination of Best Fitting Order of LH-Moments ( I ) (LH-모멘트의 적정 차수 결정에 의한 설계홍수량 추정 ( I ))

  • 맹승진;이순혁
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.6
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    • pp.49-60
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    • 2002
  • This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

Default Bayesian testing for scale parameters in the log-logistic distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.6
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    • pp.1501-1511
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    • 2015
  • This paper deals with the problem of testing on the equality of the scale parameters in the log-logistic distributions. We propose default Bayesian testing procedures for the scale parameters under the reference priors. The reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Therefore, we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference priors. To justify proposed procedures, a simulation study is provided and also, an example is given.

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.