• 제목/요약/키워드: Shapiro-Wilk W statistic

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중도절단자료에 대한 수정된 SHAPIRO-WILK 지수 검정 (A Modification of the Shapiro-Wilk Test for Exponentiality Based on Censored Data)

  • 김남현
    • 응용통계연구
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    • 제21권2호
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    • pp.265-273
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    • 2008
  • 본 논문에서는 Kim (2001a)에서 제안한 지수분포에서의 수정된 Shapiro와 Wilk (1972) $W_E$-통계량을 중도절단자료에 적용하였다. 검정통계량은 Samanta와 Schwarz (1988)에서 $W_E$-통계량을 중도절단자료에 대해 수정한 것과 같은 방법으로 정규화 등간격(normalized spacings)을 이용하여 수정하였다. 그 결과 제안된 통계량은 귀무가설에서 중도절단이 없는 경 우와 같은 분포를 갖고 표본크기만 변하게 된다. 제안된 통계량의 검정력을 Samanta와 Schwarz (1988)의 통계량과 비교한 결과, 중도절단이 없는 경우와 마찬가지로 중도절단이 있는 경우에도 변동계수가 1보다 크거나 같은 대립가설에서 제안된 통계량은 더 좋은 검정력을 나타내었다.

The Limit Distribution of a Modified W-Test Statistic for Exponentiality

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.473-481
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    • 2001
  • Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent. Kim(2001) proposed a modified Shapiro-Wilk's test statistic based on the ratio of tow asymptotically efficient estimates of scale. In this paper, we study the asymptotic behavior of the statistic using the approximation of the quantile process by a sequence of Brownian bridges and represent the limit null distribution as an integral of a Brownian bridge.

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Shapriro-Francia W' Statistic Using Exclusive Monte Carlo Simulation

  • Rahman, Mezbahur;Pearson, Larry M.
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.139-155
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    • 2000
  • An exclusive simulation study is conducted in computing means for order statistics in standard normal variate. Monte Carlo moments are used in Shapiro-Francia W' statistic computation. Finally, quantiles for Shapiro-Francia W' are generated. The study shows that in computing means for order statistics in standard normal variate, complicated distributions and intensive numerical integrations can be avoided by using Monte Carlo simulation. Lack of accuracy is minimal and computation simplicity is noteworthy.

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Consistency of a Modified W Test for Exponentiality

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.629-637
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    • 2002
  • Shapiro and Wilk(1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test based on the statistic is inconsistent Kim(2001a) proposed a modified Shapiro-Wilk's test statistic using the ratio of two asymptotically efficient estimators of scale. In this paper, we study the consistency of the proposed test.

SAMPLE ENTROPY IN ESTIMATING THE BOX-COX TRANSFORMATION

  • Rahman, Mezbahur;Pearson, Larry M.
    • Journal of the Korean Data and Information Science Society
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    • 제12권1호
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    • pp.103-125
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    • 2001
  • The Box-Cox transformation is a well known family of power transformation that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. This paper proposes a new method for estimating the Box-Cox transformation using maximization of the Sample Entropy statistic which forces the data to get closer to normal as much as possible. A comparative study of the proposed procedure with the maximum likelihood procedure, the procedure via artificial regression estimation, and the recently introduced maximization of the Shapiro-Francia W' statistic procedure is given. In addition, we generate a table for the optimal spacings parameter in computing the Sample Entropy statistic.

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NORMALIZED SAMPLE LORENZ CURVE를 이용한 검정력이 높은 정규성 검정 (More Powerful Test for Normality Based on the Normalized Sample Lorenz Curve)

  • 강석복;조영석
    • 응용통계연구
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    • 제15권2호
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    • pp.415-421
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    • 2002
  • 통계적분석에서 가장 대표적인 가정이 정규성 가정이므로 데이터의 정규성 검정은 매우 중요하다. 이 논문에서는 정규성 검정을 위해 경제학에서 소득분배의 불균형에 관한 척도로 널리 이용되는 Lorenz curve를 변형한 새로운 플롯과 검정통계량을 제시한다. 그리고 제한한 검정을 W검정 (Shapiro and Wilk (1965)), Lorenz curve를 이용한 TL검정(Kang and Cho (1999))과 몬테칼로 방법을 이용하여 검정력을 비교한다. 제안된 검정이 특별한 대립분포의 경우를 제외하고는 대부분 검정력이 높았다.

Test of Normality Based on the Transformed Lorenz Curve

  • Kang, Suk-Bok;Cho, Young-Suk
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.901-908
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    • 1999
  • Using the Transformed Lorenz curve which is introduced by Cho et al.(1999) we propose the test statistic for testing of normality that is very important test in statistical analysis and compare the proposed test statistic with the Shapiro and Wilk's W test statistic in terms of the power of test through by Monte Carlo method.

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Normal Probability Plots for Normality

  • Lee, Jea-Young;Rhee, Seong-Won
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.687-694
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    • 1999
  • The goodness of fit statistics of normality plots are obtained using the Receiver Operating Characteristic(ROC) method. This work is intended to compare with Shapiro-Wilk W statistic. Wel will use and discuss an accuracy of the test and the best cut-off value which minimizes the sum of the type I and II error probabilities.

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A note on Box-Cox transformation and application in microarray data

  • Rahman, Mezbahur;Lee, Nam-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제22권5호
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    • pp.967-976
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    • 2011
  • The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

A Modification of the W Test for Exponentiality

  • Kim, Nam-Hyun
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.159-171
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    • 2001
  • Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent ; that is, the power of the test will not approach 1 as the sample size increases. Hence we give a test based on the ratio of two asymptotically efficient estimates of scale. We also have conducted a power study to compare the test procedures, using Monte Carlo samples from a wide range of alternatives. It is found that the suggested statistics have higher power for the alternatives with the coefficient of variation greater that or equal to 1.

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