• Title/Summary/Keyword: Anderson-Darling goodness-of-fit test

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A Study on Empirical Distribution Function with Unknown Shape Parameter and Extreme Value Weight for Three Parameter Weibull Distribution (3변수 Weibull 분포형의 형상매개변수 및 극치값 가중치를 고려한 EDF 검정에 대한 연구)

  • Kim, Taereem;Shin, Hongjoon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.46 no.6
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    • pp.643-653
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    • 2013
  • The most important procedure in frequency analysis is to determine the appropriate probability distribution and to estimate quantiles for a given return period. To perform the frequency analysis, the goodness-of-fit tests should be carried out for judging fitness between obtained data from empirical probability distribution and assumed probability distribution. The previous goodness-of-fit could not consider enough extreme events from the recent climate change. In this study, the critical values of the modified Anderson-Darling test statistics were derived for 3-parameter Weibull distribution and power test was performed to evaluate the performance of the suggested test. Finally, this method was applied to 50 sites in South Korea. The result shows that the power of modified Anderson-Darling test has better than other existing goodness-of-fit tests. Thus, modified Anderson-Darling test will be able to act as a reference of goodness-of-fit test for 3-parameter Weibull model.

Goodness-of-fit test for the gumbel distribution based on the generalized Lorenz curve (일반화된 로렌츠 곡선을 기반으로 한 Gumbel 분포의 적합도 검정)

  • Lee, Kyeongjun
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.4
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    • pp.733-742
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    • 2017
  • There are many areas of applications where Gumbel distribution are employed such as environmental sciences, system reliability and hydrology. The goodness-of-fit test for Gumbel distribution is very important in environmental sciences, system reliability and hydrology data analysis. Therefore, we propose the two test statistics to test goodness-of-fit for the Gumbel distribution based on the generalized Lorenz curve. We compare the new test statistic with the Anderson - Darling test, Cramer - vonMises test, and modified Anderson - Darling test in terms of the power of the test through by Monte Carlo method. As a result, the new test statistics are more powerful than the other test statistics. Also, we propose new graphic method to goodness-of-fit test for the Gumbel distribution based on the generalized Lorenz curve.

The exponential generalized log-logistic model: Bagdonavičius-Nikulin test for validation and non-Bayesian estimation methods

  • Ibrahim, Mohamed;Aidi, Khaoula;Alid, Mir Masoom;Yousof, Haitham M.
    • Communications for Statistical Applications and Methods
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    • v.29 no.1
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    • pp.1-25
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    • 2022
  • A modified Bagdonavičius-Nikulin chi-square goodness-of-fit is defined and studied. The lymphoma data is analyzed using the modified goodness-of-fit test statistic. Different non-Bayesian estimation methods under complete samples schemes are considered, discussed and compared such as the maximum likelihood least square estimation method, the Cramer-von Mises estimation method, the weighted least square estimation method, the left tail-Anderson Darling estimation method and the right tail Anderson Darling estimation method. Numerical simulation studies are performed for comparing these estimation methods. The potentiality of the new model is illustrated using three real data sets and compared with many other well-known generalizations.

Derivation of Modified Anderson-Darling Test Statistics and Power Test for the Gumbel Distribution (Gumbel 분포형의 수정 Anderson-Darling 검정통계량 유도 및 기각력 검토)

  • Shin, Hong-Joon;Sung, Kyung-Min;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.43 no.9
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    • pp.813-822
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    • 2010
  • An important problem in frequency analysis is the estimation of the quantile for a certain return period. In frequency analysis an assumed probability distribution is fitted to the observed sample data to estimate the quantile at the upper tail corresponding to return periods which are usually much larger than the record length. In most cases, the selection of an appropriate probability distribution is based on goodness of fit tests. The goodness of fit test method can be described as a method for examining how well sample data agrees with an assumed probability distribution as its population. However it gives generally equal weight to differences between empirical and theoretical distribution functions corresponding to all the observations. In this study, the modified Anderson-Darling (AD) test statistics are provided using simulation and the power study are performed to compare the efficiency of other goodness of fit tests. The power test results indicate that the modified AD test has better rejection performances than the traditional tests. In addition, the applications to real world data are discussed and shows that the modified AD test may be a powerful test for selecting an appropriate distribution for frequency analysis when extreme cases are considered.

Tests based on EDF statistics for randomly censored normal distributions when parameters are unknown

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.26 no.5
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    • pp.431-443
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    • 2019
  • Goodness-of-fit techniques are an important topic in statistical analysis. Censored data occur frequently in survival experiments; therefore, many studies are conducted when data are censored. In this paper we mainly consider test statistics based on the empirical distribution function (EDF) to test normal distributions with unknown location and scale parameters when data are randomly censored. The most famous EDF test statistic is the Kolmogorov-Smirnov; in addition, the quadratic statistics such as the $Cram{\acute{e}}r-von$ Mises and the Anderson-Darling statistic are well known. The $Cram{\acute{e}}r-von$ Mises statistic is generalized to randomly censored cases by Koziol and Green (Biometrika, 63, 465-474, 1976). In this paper, we generalize the Anderson-Darling statistic to randomly censored data using the Kaplan-Meier estimator as it was done by Koziol and Green. A simulation study is conducted under a particular censorship model proposed by Koziol and Green. Through a simulation study, the generalized Anderson-Darling statistic shows the best power against almost all alternatives considered among the three EDF statistics we take into account.

A Study on Goodness of Fit Test in Accelerated Life Tests (가속수명시험에 대한 적합도 검정에 관한 연구)

  • Lee, Woo-Dong;Cho, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.1
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    • pp.37-46
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    • 1996
  • In this paper, we introduce the goodness of fit test procedure for lifetime distribution using step stress accelerated lifetime data. Using the nonpapametric estimate of acceleration factor, we prove the strong consistence of empirical distribution function under null hypothesis. The critical vailues of Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises statistics are computed when the lifetime distibution is assumed to be exponential and Weibull. The power of test statistics are compared through Monte-Cairo simulation study.

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An Anderson-Darling Goodness-of-Fit Test for the Gamma Distribution

  • Won, Hyung-Gyoo
    • Journal of Korean Society for Quality Management
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    • v.24 no.4
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    • pp.103-111
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    • 1996
  • This paper provides a test of the composite hypothesis that a random sample is (two parameter) gamma distributed when both the scale and shape parameters are estimated from the data. The test statistic is a variant of the usual Anderson-Darling statistic, the primary difference being that the statistic is based on the maximum likelihood estimator of the shape parameter of the assumed gamma distribution. The percentage points are developed via simulation and are presented graphically. Examples are provided.

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Goodness of Fit Testing for Exponential Distribution in Step-Stress Accelerated Life Testing (계단충격가속수명시험에서의 지수분포에 대한 적합도검정)

  • Jo, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.75-85
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    • 1994
  • In this paper, I introduce the goodness-of-fit test statistics for exponential distribution using accelerated life test data. The ALT lifetime data were obtained by assuming step-stress ALT model, specially TRV model introduced by DeGroot and Goel(1979). The critical values are obtained for proposed test statistics, Kolmogorov-Smirnov, Kuiper, Watson, Cramer-von Mises, Anderson-Darling type, under various sample sizes and significance levels. The powers of the five test statistic are compared through Monte-Cairo simulation technique.

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Goodness-of-Fit Test for the Normality based on the Generalized Lorenz Curve

  • Cho, Youngseuk;Lee, Kyeongjun
    • Communications for Statistical Applications and Methods
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    • v.21 no.4
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    • pp.309-316
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    • 2014
  • Testing normality is very important because the most common assumption is normality in statistical analysis. We propose a new plot and test statistic to goodness-of-fit test for normality based on the generalized Lorenz curve. We compare the new plot with the Q-Q plot. We also compare the new test statistic with the Kolmogorov-Smirnov (KS), Cramer-von Mises (CVM), Anderson-Darling (AD), Shapiro-Francia (SF), and Shapiro-Wilks (W) test statistic in terms of the power of the test through by Monte Carlo method. As a result, new plot is clearly classified normality and non-normality than Q-Q plot; in addition, the new test statistic is more powerful than the other test statistics for asymmetrical distribution. We check the proposed test statistic and plot using Hodgkin's disease data.

Goodness of Fit Test of Normality Based on Kullback-Leibler Information

  • Kim, Jong-Tae;Lee, Woo-Dong;Ko, Jung-Hwan;Yoon, Yong-Hwa;Kang, Sang-Gil
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.909-918
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    • 1999
  • Arizono and Ohta(1989) studied goodness of fit test of normality using the entropy estimator proposed by Vasicek (1976) Recently van Es(1992) and Correa(1995) proposed an estimator of entropy. In this paper we propose goodness of fit test statistics for normality based on Vasicek ven Es and Correa. And we compare the power of the proposed test statistics with Kolmogorov-Smirnov Kuiper Cramer von Mises Watson Anderson-Darling and Finkelstein and Schefer statistics.

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