• Title/Summary/Keyword: modified normalized sample Lorenz curve

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Invariance Properties for Statistics Based on the Sample Lorenz Curve

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.653-660
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    • 2003
  • In this paper, we prove that the transformed sample Lorenz curve, normalized sample Lorenz curve, and the test statistics for testing of normality based on the normalized sample Lorenz curve and the modified Lorenz curve which were introduced by Kang and Cho (2001a, 2002) are location and scale invariant statistics.

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Goodness-of-Fit-Test from Censored Samples

  • Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.41-52
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    • 2006
  • Because most common assumption is normality in statistical analysis, testing normality is very important. The Q-Q plot is a powerful tool to test normality with full samples in statistical package. But the plot can't test normality in type-II censored samples. This paper proposed the modified the Q-Q plot and the modified normalized sample Lorenz curve(NSLC) for normality test in the type-II censored samples. Using the two Hodgkin's disease data sets and the type-II censored samples, we picture the modified Q-Q plot and the modified normalized sample Lorenz curve.

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

  • Kang, Suk-Bok;Han, Jun-Tae
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.349-361
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    • 2009
  • In this paper, we derive the approximate maximum likelihood estimators of the shape parameter and the scale parameter in a Weibull distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We develop three modified empirical distribution function type tests for the Weibull distribution based on multiply Type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

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

  • 강석복;조영석
    • The Korean Journal of Applied Statistics
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    • v.15 no.2
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    • pp.415-421
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    • 2002
  • Because most common assumption is normality in statistical analysis, testing normality is very important. We propose a new plot and test statistic to test for normality based on the modified Lorenz curve that is proved to be a powerful tool to measure the income inequality within a population of income receivers. We also compare the proposed test statistics with the W test (Shapiro and Wilk (1965)), TL test (Kang and Cho (1999)) in terms of the power of test through by Monte Carlo method. The proposed test is more usually powerful than the other tests except some case.

Goodness-of-fit test for the logistic distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Cho, Young-Seuk
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.1
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    • pp.195-209
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    • 2014
  • In this paper, we derive the estimators of the location parameter and the scale parameter in a logistic distribution based on multiply type-II censored samples by the approximate maximum likelihood estimation method. We use four modified empirical distribution function (EDF) types test for the logistic distribution based on multiply type-II censored samples using proposed approximate maximum likelihood estimators. We also propose the modified normalized sample Lorenz curve plot for the logistic distribution based on multiply type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

Goodness-of-fit tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Seo, Yeon-Ju;Jeong, Jina
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.903-914
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    • 2014
  • The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

Goodness-of-fit test for the half logistic distribution based on multiply Type-II censored samples

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae;SaKong, Jin
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.317-325
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    • 2010
  • In this paper, we develop four modified empirical distribution function (EDF) type tests using approximate maximum likelihood estimators for the half-logistic distribution based on multiply Type-II censored samples. We also propose modified normalize sample Lorenz curve polt and new test statistics. We compare the above test statistics in the sense of the power for various censored samples. We present an example to illustrate this method.