• 제목/요약/키워드: Statistical Method

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Moments of Probability Distributions Derived Using Differential Operators

  • Kwan-Joong Kang
    • Communications for Statistical Applications and Methods
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    • 제3권1호
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    • pp.189-193
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    • 1996
  • In 1992. Boullion obtained the method of the calculus of the moments of discrete probability distributions using differential operator, and he published the method of calculus of the moments. The purpose of this paper is to introduce an idea that this method can be applied to calculate the moments of continuous probability distributions.

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On the Bias of Bootstrap Model Selection Criteria

  • Kee-Won Lee;Songyong Sim
    • Journal of the Korean Statistical Society
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    • 제25권2호
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    • pp.195-203
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    • 1996
  • A bootstrap method is used to correct the apparent downward bias of a naive plug-in bootstrap model selection criterion, which is shown to enjoy a high degree of accuracy. Comparison of bootstrap method with the asymptotic method is made through an illustrative example.

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A Combined Method Compensating for Wave Nonresponse

  • Park, Jinwoo
    • Journal of the Korean Statistical Society
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    • 제31권4호
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    • pp.469-482
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    • 2002
  • This paper suggests a new method of compensating for wave nonresponse in panel survey, which combines weighting adjustment and imputation. By deleting less frequent nonresponse patterns, we can get simplicity. A new mean estimator under the new combining method is provided and a limited simulation study employing a real data is conducted.

A CUSUM Chart Based on Log Probability Ratio Statistic

  • Park, Chang-Soon;Kim, Byung-Chun
    • Journal of the Korean Statistical Society
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    • 제19권2호
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    • pp.160-170
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    • 1990
  • A new approximation method is proposed for the ARL of CUSUM chart which is based on the log probability ratio statistic. This method uses the condition of before-stopping time to derive the expectation of excess over boundaries. The proposed method is compared to some other approximation methods in normal and exponential cases.

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STATISTICAL A-SUMMABILITY OF DOUBLE SEQUENCES AND A KOROVKIN TYPE APPROXIMATION THEOREM

  • Belen, Cemal;Mursaleen, Mohammad;Yildirim, Mustafa
    • 대한수학회보
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    • 제49권4호
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    • pp.851-861
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    • 2012
  • In this paper, we define the notion of statistical A-summability for double sequences and find its relation with A-statistical convergence. We apply our new method of summability to prove a Korovkin-type approximation theorem for a function of two variables. Furthermore, through an example, it is shown that our theorem is stronger than classical and statistical cases.

On Deferred Statistical Convergence of Sequences

  • Kucukaslan, Mehme;Yilmazturk, Mujde
    • Kyungpook Mathematical Journal
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    • 제56권2호
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    • pp.357-366
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    • 2016
  • In this paper, deferred statistical convergence is defined by using deferred $Ces{\grave{a}}ro$ mean instead of $Ces{\grave{a}}ro$ mean in the definition of statistical convergence. The obtained method is compared with strong deferred $Ces{\grave{a}}ro$ mean and statistical convergence under some certain assumptions. Also, some inclusion theorems and examples are given.

PD 분류에 있어서 핑거프린트법과 신경망의 비교 (Comparison with Finger Print Method and NN as PD Classification)

  • 박성희;박재열;이강원;강성화;임기조
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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    • pp.1163-1167
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    • 2003
  • As a PD classification method, statistical distribution parameters have been used during several ten years. And this parameters are recently finger print method, NN(Neural Network) and etc. So in this paper we studied finger print method and NN with BP(Back propagation) learning algorithm using the statistical distribution parameter, and compared with two method as classification method. As a result of comparison, classification of NN is more good result than Finger print method in respect to calculation speed, visible effect and simplicity. So, NN has more advantage as a tool for PD classification.

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Wavelet Transform based Image Registration using MCDT Method for Multi-Image

  • Lee, Choel;Lee, Jungsuk;Jung, Kyedong;Lee, Jong-Yong
    • International Journal of Internet, Broadcasting and Communication
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    • 제7권1호
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    • pp.36-41
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    • 2015
  • This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.