• Title/Summary/Keyword: reference parameter

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Reference Priors for the Location Parameter in the 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.19 no.4
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    • pp.1409-1418
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    • 2008
  • In this paper, we develop the reference priors for the common location parameter in two parameter exponential distributions. We derive the reference priors 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 prior matches the target coverage probabilities in a frequentist sense.

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Reference priors for nonregular Pareto distribution

  • 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.4
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    • pp.819-826
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    • 2011
  • In this paper, we develop the reference priors for the scale and shape parameters in the nonregular Pareto distribution. We derive the reference priors as noninformative priors and prove the propriety of joint posterior distribution under the general priors including reference priors in the order of inferential importance. Through the simulation study, we compare the reference priors with respect to coverage probabilities of parameter of interest in a frequentist sense.

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.

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.

An adaption algorithm for parallel model reference bilinear systems

  • Yeo, Yeong-Koo;Song, Hyung-Keun
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.721-723
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    • 1987
  • An Adaptation algorithm is presented and a convergence criterion is derived for parallel model reference adaptive bilinear systems. The output error converges asymptotically to zero, and the parameter estimates are bounded for stable reference models. The convergence criterion depends only upon the input sequence and a priori estimates of the maximum parameter values.

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Noninformative priors for the scale parameter in the generalized Pareto distribution

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1521-1529
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    • 2013
  • In this paper, we develop noninformative priors for the generalized Pareto distribution when the scale parameter is of interest. We developed the rst order and the second order matching priors. We revealed that the second order matching prior does not exist. It turns out that the reference prior and Jeffrey's prior do not satisfy a first order matching criterion, and Jeffreys' prior, the reference prior and the matching prior are different. Some simulation study is performed and a real example is given.

Parameter Optimization using Eevolutionary Programming in Voltage Reference Circuit Design (진화 연산을 이용한 기준 전압 회로의 파라미터 최적화)

  • 남동경;박래정;서윤덕;박철훈;김범섭
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.8
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    • pp.64-70
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    • 1997
  • This paper presents a parameter optimization method using evolutionary programming in voltage reference circuit because the designer must select appropriate parameter values of the circuit taking into consideration both powr voltage and temperature variation. In this paper, evolutionary programming is suggested as an approach for finding good parameters with which the reference voltage variation is small with respect to temperature variation. Simulation results. Simulation results show that this method is effective in circuit design.

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PARAMETER IDENTIFICATION FOR NONLINEAR VISCOELASTIC ROD USING MINIMAL DATA

  • Kim, Shi-Nuk
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.461-470
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    • 2007
  • Parameter identification is studied in viscoelastic rods by solving an inverse problem numerically. The material properties of the rod, which appear in the constitutive relations, are recovered by optimizing an objective function constructed from reference strain data. The resulting inverse algorithm consists of an optimization algorithm coupled with a corresponding direct algorithm that computes the strain fields given a set of material properties. Numerical results are presented for two model inverse problems; (i)the effect of noise in the reference strain fields (ii) the effect of minimal reference data in space and/or time data.

Noninformative priors for the reliability function of two-parameter exponential distribution

  • 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.2
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    • pp.361-369
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    • 2011
  • In this paper, we develop the reference and the matching priors for the reliability function of two-parameter exponential distribution. We derive the reference priors and the matching prior, and prove the propriety of joint posterior distribution under the general prior including the reference priors and the matching prior. Through the sim-ulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

Noninformative priors for the common shape parameter of several inverse Gaussian 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.1
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    • pp.243-253
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    • 2015
  • In this paper, we develop the noninformative priors for the common shape parameter of several inverse Gaussian distributions. Specially, we want to develop noninformative priors which satisfy certain objective criterion. The probability matching priors and reference priors of the common shape parameter will be developed. It turns out that the second order matching prior does not exist. The reference priors satisfy the first order matching criterion, but Jeffrey's prior is not the first order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.