• Title/Summary/Keyword: Distribution data

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Statistical Relation between Worst Month and Annual Distribution for Rainfall Rate (강우강도 최악월 분포와 년 분포간의 상관관계 분석)

  • 이주환;최용석김재명
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.203-206
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    • 1998
  • Since it has been very difficult to collect Korean rain data for winter season, e.g. from November to March, it would be very useful to design satellite communication links if there is a method to extract annual distribution from rain data collected for a specific month. This paper presents a conversion method to annual rainfall rate distribution from rain data for worst month of a year, and illustrates some analysis of the conversion results.

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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.

The development feasibility of MMI for automated distribution systems (배전자동화 시스템용 MMI 개발 가능성)

  • 류재택;박세응
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.107-112
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    • 1990
  • It is necessary to develop graphic MMI (Man-Machine Interface) for the maximum utilization of our installed ADS (Automated Distribution System) for which an operator types and executes string commands. Considering the restrictions and characteristics of the installed ADS and the data for modelled distribution lines, we calculated the time of periodic data acquisition for large number of points. And we presented the performance and characteristics of the graphic MMI system which will be developed and which will facilitate SCADA(Supervisory Control And Data Acquisition) functions.

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Hierarchical classification of Fingerprints using Discrete Wavelet Transform (이산 웨이블릿 변환을 이용한 지문의 계층적 분류)

  • Kwon, Yong-Ho;Lee, Jung-Moon
    • Journal of Industrial Technology
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    • v.19
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    • pp.403-408
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    • 1999
  • An efficient method is developed for classifying fingerprint data based on 2-D discrete wavelet transform. Fingerprint data is first converted to a binary image. Then a multi-level 2-D wavelet transform is performed. Vertical and horizontal subbands of the transformed data show typical energy distribution patterns relevant to the fingerprint categories. The proposed method with moderate level of wavelet transform is successful in classifying fingerprints into 5 different types. Finer classification is possible by higher frequency subbands and closer analysis of energy distribution.

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Empirical Bayes Inferences in the Burr Distribution by the Bootstrap Methods

  • Cho, Kil-Ho;Cho, Jang-Sik;Jeong, Seong-Hwa;Shin, Jae-Seock
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.625-632
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    • 2004
  • We consider the empirical Bayes confidence intervals that attain a specified level of EB coverage for the scale parameter in the Burr distribution under type II censoring data. Also, we compare the coverage probabilities and the expected confidence interval lengths for these confidence intervals through simulation study.

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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.

Goodness-of-fit Test for the Extreme Value Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1441-1448
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    • 2008
  • We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

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Estimation in Mixture of Shifted Poisson Distributions with Known Shift Parameters

  • Lee, Hyun-Jung;Oh, Chang-Hyuck
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.785-794
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    • 2006
  • Suggested is an EM algorithm for estimation in mixture of shifted Poisson distributions with known shift parameters. For this type of mixture distribution, we have to utilize values of shift parameters to determine whether each of data belongs to some component distribution. We propose a method of estimating values of component information and then follow typical EM methodology. Simulation results show that the algorithm provides reasonable performance for the distribution.

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Exponential family of circular distributions

  • Kim, Sung-Su
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1217-1222
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    • 2011
  • In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.