• 물과 미래
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• 제7권2호
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• pp.99-106
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• 1974

The records of wave heights which were observed at Muk ho and Po hang of the East Coast of Korea were analized by several probility functions. The exponential 2 parameter distribution was found as the best fit probability function to the historical distribution of wave heights by the test of goodness of fit. But log-normal 2 parameter and log-extremal type A distributions were also fit to the historical distribution, especially in the Smirnov-Kolmogorov test. Therefore, it can't be always regarded that those two distributions are not fit to the wave heiht's distribution. In the test of goodness of fit, the Chi-Square test gave very sensitive results and Smirnov-Kolmogorov test, which is a distribution free and non-parametric test, gave more inclusive results. At the next stage, the inter-relationship between the mean and the one-third wave heights, the mean and the one-=tenth wave heights, the one-third and the one-tenth wave heights, the one-third and the highest wave heights were obtained and discussed.

• Communications for Statistical Applications and Methods
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• 제24권5호
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• pp.519-531
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• 2017

We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.37-46
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• 1996

계단충격가속수명시험에서 얻은 자료를 토대로 통계적 추론을 위해 가정하는 수명분포에 대한 적합도 검정을 Kolmogorov-Smirnov, Cramer-von Mises, Anderson-Darling과 같은 비모수적 검정통계량들을 이용한 검정절차를 제안하고, 각 통계량들을 검정력 측면에서 비교하고자 한다.

• 한국통신학회논문지
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• 제39C권9호
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• pp.852-860
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• 2014

본 논문에서 임펄스성 잡음의 유무를 검증하는 알고리즘을 제안한다. 본 알고리즘을 제안하는 이유는 기존의 Kolmogorov-Smirnov 검증의 단점으로 낮은 분류 성공률 및 높은 복잡도가 있기 때문이다. 이는 이론적으로 문제가 없으나 실제로 구현함에 있어 많은 문제를 야기한다. 먼저 기존의 검증 방법을 설명 후 제안하는 알고리즘을 설명한다. 이 알고리즘은 기존의 Kolmogorov-Smirnov 검증 방법의 이론적 배경으로부터 제안된다. 알고리즘의 효율성을 증명하기 위해 임펄스성 잡음의 샘플을 이용하여 실험 후, 검증 실패 확률을 조사한다. 검증 실패 확률에 기반한 실험 결과는 제안한 알고리즘의 효율성을 증명한다.

• Journal of the Korean Data and Information Science Society
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• 제5권2호
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• pp.75-85
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• 1994

계단 충격 가속수명시험에서 통계적 추론을 위해 가정하는 수명분포에 대한 적합도검정을 Kolmogorov-Smirnov, Kuiper, Watson, Cramer-von Mises, Anderson-Darling과 같은 비모수적 검정통계량에 대하여 몬테칼로 방법을 이용한 기각치를 구하고, 검정력 측면에서 비교, 연구한다.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.259-268
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• 2006

For Type-II censored sample, we propose three modified entropy estimators based on the Vasieck's estimator, van Es' estimator, and Correa's estimator. We also propose the goodness-of-fit tests of the Weibull distribution based on the modified entropy estimators. We simulate the mean squared errors (MSE) of the proposed entropy estimators and the powers of the proposed tests. We also compare the proposed tests with the modified Kolmogorov-Smirnov and Cramer-von-Mises tests which were proposed by Kang et al. (2003).

• Journal of the Korean Data and Information Science Society
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• 제6권1호
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• pp.31-37
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• 1995

We consider density estimates of the usual type generated by a kernel function. By using the limit theorems for the maximum of normalized deviation of the estimate from its expected value, we propose to use data dependent bandwidth in the tests of goodness of fit based on these statistics. Also a small sample Monte Carlo simulation is conducted and proposed method is compared with Kolmogorov-Smirnov test.

• Communications for Statistical Applications and Methods
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• 제4권2호
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• pp.435-444
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• 1997

The objective of this study is to investigate the problem of goodness of fit testing based on nonparametric function estimation techniques for the random censorship model. The small and large sample properties of the proposed test, $E_{mn}$, were investigated and it is shown that under the proportional hazard model $E_{mn}$ has higher power compared to the powers of the Kolmogorov -Smirnov, Kuiper, Cramer-von Mises, and analogue of the Cramer-von Mises type test statistic.

• Communications for Statistical Applications and Methods
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• 제21권4호
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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.

• Communications for Statistical Applications and Methods
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• 제26권5호
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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.