• Title/Summary/Keyword: 척도모수

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Bayesian Estimation of k-Population Weibull Distribution Under Ordered Scale Parameters (순서를 갖는 척도모수들의 사전정보 하에 k-모집단 와이블분포의 베이지안 모수추정)

  • 손영숙;김성욱
    • The Korean Journal of Applied Statistics
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    • v.16 no.2
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    • pp.273-282
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    • 2003
  • The problem of estimating the parameters of k-population Weibull distributions is discussed under the prior of ordered scale parameters. Parameters are estimated by the Gibbs sampling method. Since the conditional posterior distribution of the shape parameter in the Gibbs sampler is not log-concave, the shape parameter is generated by the adaptive rejection sampling. Finally, we applied this estimation methodology to the data discussed in Nelson (1970).

척도모수에 대한 비모수적 검정법에 관한 연구

  • 김동재
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.169-178
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    • 1996
  • 일반적인 실험군과 대조군의 척도모수에 대한 가설을 Orban과 Wolfe(1982)가 도입한 placement를 이용하여 비모수적 검정법을 제안하였다. 위치모수를 알고 있는 경우에 제안된 통계량의 귀무가설하에서의 평균과 분산 그리고 반복점근분포(iterative asymptotic distribution)를 구하였고 기존의 검정법들과 소표본 모의실험을 통하여 실험 유의수준과 실험검정력을 비교하였다.

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지수분포의 검정을 위한 수정된 W-통계량

  • 김남현
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.141-146
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    • 2000
  • Shapiro와 Wilk(1972)는 위치모수와 척도모수가 미지인 경우 지수분포의 검정통계량을 제안하였다. 그것은 척도모수의 일반화 최소제곱추정량과 표본분산의 비로 구성되었다. 그러나 이 검정통계량은 일치성을 갖지 않는다. 본 논문에서는 척도모수의 두개의 점근유효추정량으로 구성된 통계량을 고려하고 이의 극한분포를 구하였다. 또한 두 개의 통계량의 검정력을 비교한 결과 제안된 통계량이 변동계수가 1보다 크거나 같은 분포에서 더 좋은 검정력을 가짐을 볼 수 있었다.

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Optimal design of a nonparametric Shewhart-Lepage control chart (비모수적 Shewhart-Lepage 관리도의 최적 설계)

  • Lee, Sungmin;Lee, Jaeheon
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.339-348
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    • 2017
  • One of the major issues of statistical process control for variables data is monitoring both the mean and the standard deviation. The traditional approach to monitor these parameters is to simultaneously use two seperate control charts. However there have been some works on developing a single chart using a single plotting statistic for joint monitoring, and it is claimed that they are simpler and may be more appealing than the traditonal one from a practical point of view. When using these control charts for variables data, estimating in-control parameters and checking the normality assumption are the very important step. Nonparametric Shewhart-Lepage chart, proposed by Mukherjee and Chakraborti (2012), is an attractive option, because this chart uses only a single control statistic, and does not require the in-control parameters and the underlying continuous distribution. In this paper, we introduce the Shewhart-Lepage chart, and propose the design procedure to find the optimal diagnosis limits when the location and the scale parameters change simultaneously. We also compare the efficiency of the proposed method with that of Mukherjee and Chakraborti (2012).

깁스표본기법을 이용한 와이블분포의 모수추정

  • 이우동;이창순;강상길
    • Journal of Korea Society of Industrial Information Systems
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    • v.3 no.1
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    • pp.13-21
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    • 1998
  • 와이블분포의 척도모수와 형상모수를 베이지안 방법을 이용하여 추정한다. 깁스표본법을 사용하여 모수들에 대한 추정, 결합사후확률분포와 주변사후확률분포를 구한다. 9개의 열 전달기기자료와 10개의 인위적인 자료를 이용하여 제안된 방법을 적용하여 사례를 연구한다.

An Estimation of Parameters in Weibull Distribution using Gibbs Sampler (깁스표본기법을 이용한 와이블분포의 모수추정)

  • 이우동;이창순;강상길
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1997.11a
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    • pp.521-533
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    • 1997
  • 와이블분포에서 척도모수와 형상모수를 베이지안 방법을 이용하여 추정한다. 깁스표본법을 사용하여 모수들에 대한 추정, 결합사후확률분포 와 주변사후확률분포를 구한다. 9개의 열 전달기기자료와 10개의 인위적인 자료를 이용하여 제안된 방법을 적용하여 사례를 연구한다.

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Optimal Design of Lognormal Accelerated Life Tests with Nonconstant Scale Parameter (스트레스에 의존하는 척도모수를 가진 대수정규 가속수명시험의 최적설계)

  • Park, Byung-Gu;Yoon, Sang-Chul;Seo, Ho-Cheol
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.1
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    • pp.47-57
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    • 1996
  • This paper on planning constant accelerated life test is assumed that parameters for a lognormal life distribution are depended on changes of stresses. The proposed test plans are optimum in that they minimize the asymptotic variance of maximum likelihood estimator of a specified quantile at the design stress. The optimal amount of low stress level ${\xi}_{L}$ and optimal sample proportion ${\pi}$ to be allocated at low stress level are obtained when the ratio of scales at high stress level and design stress level is unknown.

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A simulation comparison on the analysing methods of Likert type data (모의실험에 의한 리커트형 설문분석 방법의 비교)

  • Kim, Hyun Chul;Choi, Seung Kyoung;Choi, Dong Ho
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.2
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    • pp.373-380
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    • 2016
  • Even though Likert type data is ordinal scale, many researchers who regard Likert type data as interval scale adapt as parametric methods. In this research, simulations have been used to find out a proper analysis of Likert type data. The locations and response distributions of five point Likert type data samples having diverse distribution have been evaluated. In estimating samples' locations, we considered parametric method and non-parametric method, which are t-test and Mann-Whitney test respectively. In addition, to test response distribution, we employed Chi-squared test and Kolmogorov-Smirnov test. In this study, we assessed the performance of the four aforementioned methods by comparing Type I error ratio and statistical power.

Kullback-Leibler Information-Based Tests of Fit for Inverse Gaussian Distribution (역가우스분포에 대한 쿨백-라이블러 정보 기반 적합도 검정)

  • Choi, Byung-Jin
    • The Korean Journal of Applied Statistics
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    • v.24 no.6
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    • pp.1271-1284
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    • 2011
  • The entropy-based test of fit for the inverse Gaussian distribution presented by Mudholkar and Tian(2002) can only be applied to the composite hypothesis that a sample is drawn from an inverse Gaussian distribution with both the location and scale parameters unknown. In application, however, a researcher may want a test of fit either for an inverse Gaussian distribution with one parameter known or for an inverse Gaussian distribution with both the two partameters known. In this paper, we introduce tests of fit for the inverse Gaussian distribution based on the Kullback-Leibler information as an extension of the entropy-based test. A window size should be chosen to implement the proposed tests. By means of Monte Carlo simulations, window sizes are determined for a wide range of sample sizes and the corresponding critical values of the test statistics are estimated. The results of power analysis for various alternatives report that the Kullback-Leibler information-based goodness-of-fit tests have good power.

k-Sample Rank Tests for Umbrella Location-Scale Alternatives (k-표본 우산형 위치-척도 대립가설에 대한 순위검정법의 연구)

  • Hee Moon Park
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.159-171
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    • 1994
  • Some rank score tests are proposed for testing the equality of all sampling distribution functions against umbrella location-scale alternatives in k-sample problem. Only the case of known peak $\ell$ is considered. Under the null hypothesis and a contiguous sequence of unbrella location-scale alternatives, the asymptotic properties of the proposed test statistics are investigated. Also, the asymptotic local powers are compared with each others. The results show that the tests based on the Chen-Wolfe rank analogue statistic are more powerful than others for unequally spaced umbrella location-scale alternatives and robust.

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