• Title/Summary/Keyword: Distribution Information

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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.

Moment of the ratio and approximate MLEs of parameters in a bivariate Pareto distribution

  • Kim, Jungdae
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1213-1222
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    • 2012
  • We shall derive the moment of the ratio Y/(X + Y) and the reliability P(X < Y ), and then observe the skewness of the ratio in a bivariate Pareto density function of (X, Y). And we shall consider an approximate MLE of parameters in the bivariate Pareto density function.

On the Support Vector Machine with the kernel of the q-normal distribution

  • Joguchi, Hirofumi;Tanaka, Masaru
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.983-986
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    • 2002
  • Support Vector Machine (SVM) is one of the methods of pattern recognition that separate input data using hyperplane. This method has high capability of pattern recognition by using the technique, which says kernel trick, and the Radial basis function (RBF) kernel is usually used as a kernel function in kernel trick. In this paper we propose using the q-normal distribution to the kernel function, instead of conventional RBF, and compare two types of the kernel function.

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A NOVEL UNSUPERVISED DECONVOLUTION NETWORK:EFFICIENT FOR A SPARSE SOURCE

  • Choi, Seung-Jin
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.336-338
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    • 1998
  • This paper presents a novel neural network structure to the blind deconvolution task where the input (source) to a system is not available and the source has any type of distribution including sparse distribution. We employ multiple sensors so that spatial information plays a important role. The resulting learning algorithm is linear so that it works for both sub-and super-Gaussian source. Moreover, we can successfully deconvolve the mixture of a sparse source, while most existing algorithms [5] have difficulties in this task. Computer simulations confirm the validity and high performance of the proposed algorithm.

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A Note on the Population Center of Korea (인구중심의 변천에 관한 연구)

  • Yang, Jae Young;Lee, Nak Young
    • Journal of Applied Reliability
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    • v.15 no.3
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    • pp.192-196
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    • 2015
  • It is important to obtain the information of population center for establishing the balanced development policy of a nation. In this note, the population center of Korea is obtained using 2010 Census data and compared with the past population centers. The weighted average method is used for calculating the population center. The results of this note will be able to contribute in the regional population distribution policies.

Reliability for Series System in Bivariate Weibull Model under Bivariate Random Censorship

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.219-226
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    • 2004
  • In this paper, we consider two-components system which the lifetimes have a bivariate Weibull distribution with bivariate random censored data. Here the bivariate censoring times are independent of the lifetimes of the components. We obtain estimators and approximated confidence intervals for the reliability of series system based on likelihood function and relative frequency, respectively. Also we present a numerical study.

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Notes on the Comparative Study of the Reliability Estimation for Standby System with Rayleigh Lifetime Distribution

  • Kim, Hee-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.239-250
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    • 2004
  • We shall propose maximum likelihood, Bayesian and generalized maximum likelihood estimation for the reliability of the two-unit hot standby system with Rayleigh lifetime distribution that switch is perfect. Each estimation will be compared numerically in terms of various mission times, parameter values and asymptotic relative efficiency through Monte Carlo simulation.

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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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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.

Analysis on Trends of Artworks Blockchain Platform

  • Lee, Yo-Seob
    • International Journal of Advanced Culture Technology
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    • v.7 no.3
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    • pp.149-157
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    • 2019
  • Recently, the blockchain platform is changing the art market. Changes are taking place in many areas, including artists, collectors, art investors, and auction. The platform that provides distribution history information on artworks on a blockchain basis can be used when information on the work history is suspected or needs verification, and can be used to manage the distribution history information of stolen and lost artworks and confiscated artworks by the police. Several companies currently operate these platforms, but they operate various blockchain platforms according to their contents. In this paper, we will compare and analyze features of artworks blockchain platform.