• Title/Summary/Keyword: 우도비검정

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Likelihood Ratio Test for the Epidemic Alternatives on the Zero-Inflated Poisson Model (변화시점이 있는 영과잉-포아송모형에서 돌출대립가설에 대한 우도비검정)

  • Kim, Kyung-Moo
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.247-253
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    • 1998
  • In ease of the epidemic Zero-Inflated Poisson model, likelihood ratio test was used for testing epidemic alternatives. Epidemic changepoints were estimated by the method of least squares. It were used for starting points to estimate the maximum likelihood estimators. And several parameters were compared through the Monte Carlo simulations. As a result, maximum likelihood estimators for the epidemic chaagepoints and several parameters are better than the least squares and moment estimators.

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이변량 지수모형의 독립성검정

  • 김정일
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.549-556
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    • 1997
  • 본 논문에서는 Block과 Basu (1974)가 제안한 절대연속이변량지수분포(absolutely continuous bivariate exponential distribution : ACBVED)의 독립성검정에 대한 Score검정과 이 검정의 점근성을 높이기 위하여 Cordeiro와 Ferrari (1991)가 제시한 Bartlett수정항과 유사한 형태의 수정된 Score검정을 유도하였다. 그리고 수정된 Score검정의 점근성의 효과와 주변분포가 동일하다는 가정하에서 Gupta, Mehrotra와 Michalek (1984)가 제안한 우도비검정을 모의실험으로 비교하였다.

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일반화 감마분포에서의 누율계산과 지표모수에 대한 Bartlett 검정

  • 나종화
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.533-540
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    • 1997
  • 일반화 감마분포(generalized gamma distribution)에서 지표모수(index parameter)에 대한 추론은 생존시간(lifetime)과 관련한 모형의 선택문제에서 매우 중요하다. 이에 대한 정확한(exact) 추론법은 알려져 있지 않다. 본 연구에서는 이에 대한 점근적(asymptotic) 검정법으로 소표본에서도 우도비 검정에 비해 효율이 뛰어난 Bartlett 검정을 제안하고, 이의 요율적 수행을 위한 대체 모형으로 부터의 누율계산(cumulant computation) 법을 제시하였다. 또한 실제자료에 대해 본 논문에서 제시한 누율계산과정을 이용하여 Bartlett 검정을 실시한 결과 기존의 우도비 검정과는 상당히 큰 차이가 남을 확인하였다. 따라서 모형의 선택 등의 문제에서 제안된 방법은 소표본의 경우에 더욱 효율적이라 할 수 있다.

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Statistical methods for Edge Detection in Images (영상에서 에지 검출을 위한 통계적 방법)

  • 임동훈;박은희
    • The Korean Journal of Applied Statistics
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    • v.13 no.2
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    • pp.515-523
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    • 2000
  • In this paper we detect edges using stutistical methods of the change-point problem. For this, we perform the hypothesis testing for differences in gray levels to see whether any $n\timesn$ subimage contains edge segments. The proposed method based on the twosample Kolmogorov-Smirnov test is introduced and the likelihood ratio test and the \VolfeSchechtman test for change-point problem arc also applied for edge detection. \Ve perform the experimental study to assess the performance of these methods in both noisy and uncontaminated sample noises.

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On Tests for Marginal Homogeneity (주변동질성 검정법의 비교분석)

  • 강민희;박태성;이성곤
    • The Korean Journal of Applied Statistics
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    • v.14 no.1
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    • pp.211-221
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    • 2001
  • 본 논문에서는 2$\times$2 분할표의 주변동질성 검정에서 사용될 수 있는 통계량들을 소개하고, 이 통계량들을 비교하였다. 먼저 주변동질성 검정에 민감하게 영향을 주는 모수를 정의한 후에 이 모수들의 효과를 예시하였다. 또한 이 모수들을 이용하여 모의실험을 통해여러 검정법들을 비교해본 결과 McNemar 검정이 다른 검정력보다 더 좋은 성질을 가지고 있음을 보였다.

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The likelihood ratio test for detecting the best treatment among several exponential populations (지수분표에 있어서 최우수 처리의 판별을 위한 우도비 검정)

  • 황형태
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.151-157
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    • 1995
  • The method for detecting the best treatment is considered by means of hypothesis testing in the exponential case. The likelihood ratio test for a given hypothesis is derived to control the error probability, and the minimum powers in the interested regions are calculated to design the sampling plan.

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A Generalized Likelihood Ratio Test in Outlier Detection (이상점 탐지를 위한 일반화 우도비 검정)

  • Jang Sun Baek
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.225-237
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    • 1994
  • A generalized likelihood ratio test is developed to detect an outlier associated with monitoring nuclear proliferation. While the classical outlier detection methods consider continuous variables only, our approach allows both continuous and discrete variables or a mixture of continuous and discrete variables to be used. In addition, our method is free of the normality assumption, which is the key assumption in most of the classical methods. The proposed test is constructed by applying the bootstrap to a generalized likelihood ratio. We investigate the performance of the test by studying the power with simulations.

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Target Detection Performance in a Clutter Environment Based on the Generalized Likelihood Ratio Test (클러터 환경에서의 GLRT 기반 표적 탐지성능)

  • Suh, Jin-Bae;Chun, Joo-Hwan;Jung, Ji-Hyun;Kim, Jin-Uk
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.5
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    • pp.365-372
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    • 2019
  • We propose a method to estimate unknown parameters(e.g., target amplitude and clutter parameters) in the generalized likelihood ratio test(GLRT) using maximum likelihood estimation and the Newton-Raphson method. When detecting targets in a clutter environ- ment, it is important to establish a modular model of clutter similar to the actual environment. These correlated clutter models can be generated using spherically invariant random vectors. We obtain the GLRT of the generated clutter model and check its detection probability using estimated parameters.

Zero-Inflated Poisson Model with a Change-point (변화시점이 있는 영과잉-포아송모형)

  • Kim, Kyung-Moo
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.1
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    • pp.1-9
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    • 1998
  • In case of Zero-Inflated Poisson model with a change-point, likelihood ratio test statistic was used for testing hypothesis for a change-point. A change-point and several interesting parameters were estimated by using the method of moments and maximum likelihood. In order to compare the estimators, empirical mean-square-error was used. Real data for the Zero-Inflated Poisson model with a change-point and Poisson model without a change-point were examined.

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Fuzzy Test of Hypothesis by Uniformly Most Powerful Test (균일최강력검정에 의한 가설의 퍼지 검정)

  • Kang, Man-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.25-28
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    • 2011
  • In this paper, we study some properties of condition for fuzzy data, agrement index by ratio of area and the uniformly most powerful fuzzy test of hypothesis. Also, we suggest a confidence bound for uniformly most powerful fuzzy test. For illustration, we take the most powerful critical fuzzy region from exponential distribution by likelihood ratio and test the hypothesis of ${\chi}^2$-distribution by agreement index.