• Title/Summary/Keyword: Kolmogorov-Smirnov goodness-of-fit test

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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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Exponentiality Test of the Three Step-Stress Accelerated Life Testing Model based on Kullback-Leibler Information

  • Park, Byung-Gu;Yoon, Sang-Chul;Lee, Jeong-Eun
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.951-963
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    • 2003
  • In this paper, we propose goodness of fit test statistics based on the estimated Kullback-Leibler information functions using the data from three step stress accelerated life test. This acceleration model is assumed to be a tampered random variable model. The power of the proposed test under various alternatives is compared with Kolmogorov-Smirnov statistic, Cramer-von Mises statistic and Anderson-Darling statistic.

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Test of Exponentiality in Step Stress Accelerated Life test Model based on Kullback­Leibler Information Function (쿨백­라이블러 정보함수 이용한 단계 스트레스 가속수명모형의 지수성 검정)

  • 박병구;윤상철
    • Journal of Korean Society for Quality Management
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    • v.31 no.4
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    • pp.194-202
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    • 2003
  • In this paper, we propose goodness of fit test statistics for exponentiality in accelerated life tests data based on Kullback­Leibler information functions. This acceleration model is assumed to be a tampered random variable model. The procedure is applicable when the exponential parameter using the data from accelerated life tests is or is not specified under null hypothesis. And we compare the power of the proposed test statistics with Kolmogorov­Smirnov, Cramer von Mises and Anderson­Darling statistics in the small sample.

Power comparison of distribution-free two sample goodness-of-fit tests (이표본 분포 동일성에 대한 분포무관 검정법 간 검정력 비교 연구)

  • Kim, Seon Bin;Lee, Jae Won
    • The Korean Journal of Applied Statistics
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    • v.30 no.4
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    • pp.513-528
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    • 2017
  • Statistics are often used to test two samples if they have been drawn from the same underlying distribution. In this paper, we introduce several well-known distribution-free tests to compare distributions and conduct an extensive Monte-Carlo simulation to specify their behaviors. We consider various circumstances of when two distributions vary in (1) location, (2) scale, (3) symmetry, (4) kurtosis, (5) tail weight. A practical guideline for two-sample goodness-of-fit test is presented based on the simulation result.

Classical and Bayesian methods of estimation for power Lindley distribution with application to waiting time data

  • Sharma, Vikas Kumar;Singh, Sanjay Kumar;Singh, Umesh
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.193-209
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    • 2017
  • The power Lindley distribution with some of its properties is considered in this article. Maximum likelihood, least squares, maximum product spacings, and Bayes estimators are proposed to estimate all the unknown parameters of the power Lindley distribution. Lindley's approximation and Markov chain Monte Carlo techniques are utilized for Bayesian calculations since posterior distribution cannot be reduced to standard distribution. The performances of the proposed estimators are compared based on simulated samples. The waiting times of research articles to be accepted in statistical journals are fitted to the power Lindley distribution with other competing distributions. Chi-square statistic, Kolmogorov-Smirnov statistic, Akaike information criterion and Bayesian information criterion are used to access goodness-of-fit. It was found that the power Lindley distribution gives a better fit for the data than other distributions.

Differences by Selection Method for Exposure Factor Input Distribution for Use in Probabilistic Consumer Exposure Assessment

  • Kang, Sohyun;Kim, Jinho;Lim, Miyoung;Lee, Kiyoung
    • Journal of Environmental Health Sciences
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    • v.48 no.5
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    • pp.266-271
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    • 2022
  • Background: The selection of distributions of input parameters is an important component in probabilistic exposure assessment. Goodness-of-fit (GOF) methods are used to determine the distribution of exposure factors. However, there are no clear guidelines for choosing an appropriate GOF method. Objectives: The outcomes of probabilistic consumer exposure assessment were compared by using five different GOF methods for the selection of input distributions: chi-squared test, Kolmogorov-Smirnov test (K-S), Anderson-Darling test (A-D), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Methods: Individual exposures were estimated based on product usage factor combinations from 10,000 respondents. The distribution of individual exposure was considered as the true value of population exposures. Results: Among the five GOF methods, probabilistic exposure distributions using the A-D and K-S methods were similar to individual exposure estimations. Comparing the 95th percentiles of the probabilistic distributions and the individual estimations for 10 CPs, there were 0.73 to 1.92 times differences for the A-D method, and 0.73 to 1.60 times differences (excluding tire-shine spray) for the K-S method. Conclusions: There were significant differences in exposure assessment results among the selection of the GOF methods. Therefore, the GOF methods for probabilistic consumer exposure assessment should be carefully selected.

Characteristics of Probability Distribution of BOD Concentration in Anseong Stream Watershed (안성천 유역의 BOD농도 확률분포 특성)

  • Kim, Kyung Sub;Ahn, Taejin
    • Journal of Korean Society on Water Environment
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    • v.25 no.3
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    • pp.425-431
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    • 2009
  • It is very important to know the probability distribution of water-quality constituents for water-quality control and management of rivers and reservoirs effectively. The probability distribution of BOD in Anseong Stream was analyzed in this paper using Kolmogorov-Smirnov test which is widely used goodness-of-fit method. It was known that the distribution of BOD in Anseong Stream is closer to Log-normal, Gamma and Weibull distributions than Normal distribution. Normal distribution can be partially applied depending on significance level, but Log-normal, Gamma and Weibull distributions can be used in any significance level. Also the estimated Log-normal distribution of BOD at Jinwi3 station was to be compared with the measured in 2001, 2002 and 2003 years. It was revealed that the estimated probability distribution of BOD at Jinwi3 follows a theoretical distribution very well. The applicable probability distribution of BOD can be used to explain more rigorously and scientifically the achievement or violation of target concentration in TMDL(Total Maximum Daily Load).

Precision Validation of Electromagnetic Physics in Geant4 Simulation for Proton Therapy (양성자 치료 전산모사를 위한 Geant4 전자기 물리 모델 정확성 검증)

  • Park, So-Hyun;Rah, Jeong-Eun;Shin, Jung-Wook;Park, Sung-Yong;Yoon, Sei-Chul;Jung, Won-Gyun;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.20 no.4
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    • pp.225-234
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    • 2009
  • Geant4 (GEometry ANd Tracking) provides various packages specialized in modeling electromagnetic interactions. The validation of Geant4 physics models is a significant issue for the applications of Geant4 based simulation in medical physics. The purpose of this study is to evaluate accuracy of Geant4 electromagnetic physics for proton therapy. The validation was performed both the Continuous slowing down approximation (CSDA) range and the stopping power. In each test, the reliability of the electromagnetic models in a selected group of materials was evaluated such as water, bone, adipose tissue and various atomic elements. Results of Geant4 simulation were compared with the National Institute of Standards and Technology (NIST) reference data. As results of comparison about water, bone and adipose tissue, average percent difference of CSDA range were presented 1.0%, 1.4% and 1.4%, respectively. Average percent difference of stopping power were presented 0.7%, 1.0% and 1.3%, respectively. The data were analyzed through the kolmogorov-smirnov Goodness-of-Fit statistical analysis test. All the results from electromagnetic models showed a good agreement with the reference data, where all the corresponding p-values are higher than the confidence level $\alpha=0.05$ set.

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A Statistical Analysis on Fatigue Life Distribution in Spheroidal Graphite Cast Iron (구상흑연주철의 피로수명분포에 대한 통계적 해석)

  • Jang, Seong-Su;Kim, Sang-Tae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.9 s.180
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    • pp.2353-2360
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    • 2000
  • Statistical fatigue properties of metallic materials are increasingly required for reliability design purpose. In this study, static and fatigue tests were conducted and the normal, log-normal, two -parameter Weibull distributions at the 5% significance level are compared using the Kolmogorov-Smirnov goodness-of-fit test. Parameter estimation were compared with experimental results using the maximum likelihood method and least square method. It is found that two-parameter Weibull distribution and maximum likelihood method provide a good fit for static and fatigue life data. Therefore, it is applicable to the static and fatigue life analysis of the spheroidal graphite cast iron. The P-S-N curves were evaluated using log-normal distribution, which showed fatigue life behavior very well.

Failure Probability Models of Concrete Subjected to Split Tension Repeated- Loads (쪼갬인장 반복하중을 받는 콘크리트의 파괴확률 모델)

  • 김동호;김경진;이봉학;윤경구
    • Proceedings of the Korea Concrete Institute Conference
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    • 2003.05a
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    • pp.311-314
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    • 2003
  • Concrete structures such as bridge, pavement, airfield, and offshore structure are normally subjected to repeated load. This paper proposes a failure probability models of concrete subjected to split tension repeated-loads, based on experimental results. The fatigue tests were performed at the stress ratio of 0.1, the loading shape of sine, the frequency of 20Hz, and the stress levels of 90, 80 and 70%. The fatigue test specimen was 150mm in diameter and 75mm in thickness. The fatigue analysis did not include which exceeded 0.9 of statistical coefficient of determination values or did not failure at 2$\times$$10^6$ cycles. The graphical method, the moment method, and maximum likelihood estimation method were used to obtain Weibull distribution parameters. The goodness-of-fit test by Kolmogorov-Smirnov test was acceptable 5% level of significance. As a result, the proposed failure probability model based on the two-parameter($\alpha and \mu$) Weibull distribution was good enough to estimate accurately the fatigue life subjected to tension mode.

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