• Title/Summary/Keyword: 적합도 검정

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A Test of Fit for Inverse Gaussian Distribution Based on the Probability Integration Transformation (확률적분변환에 기초한 역가우스분포에 대한 적합도 검정)

  • Choi, Byungjin
    • The Korean Journal of Applied Statistics
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    • v.26 no.4
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    • pp.611-622
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    • 2013
  • Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)'s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.

Goodness-of-fit test for normal distribution based on parametric and nonparametric entropy estimators (모수적 엔트로피 추정량과 비모수적 엔트로피 추정량에 기초한 정규분포에 대한 적합도 검정)

  • Choi, Byungjin
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.847-856
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    • 2013
  • In this paper, we deal with testing goodness-of-fit for normal distribution based on parametric and nonparametric entropy estimators. The minimum variance unbiased estimator for the entropy of the normal distribution is derived as a parametric entropy estimator to be used for the construction of a test statistic. For a nonparametric entropy estimator of a data-generating distribution under the alternative hypothesis sample entropy and its modifications are used. The critical values of the proposed tests are estimated by Monte Carlo simulations and presented in a tabular form. The performance of the proposed tests under some selected alternatives are investigated by means of simulations. The results report that the proposed tests have better power than the previous entropy-based test by Vasicek (1976). In applications, the new tests are expected to be used as a competitive tool for testing normality.

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.

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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A Study On Variance Estimation in Smoothing Goodness-of-Fit Tests (평활 적합도 검정에서의 분산추정의 영향)

  • Yoon, Yong-Hwa;Kim, Jong-Tae;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.189-202
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    • 1998
  • The goat of this paper is to study on variance estimation - Rice variance estimation, Gasser, Sroka and Jennen-Steinmetz's varince estimation - in smoothing goodness-of-fit tests. The comparisons of powers on test statistics are conducted by the change of variance, the number of oscillations, the amplitude of the alternative sample distribution.

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시계열 모형의 적합도 검정에 관한 시뮬레이션 연구

  • 이성덕;차경엽
    • Communications for Statistical Applications and Methods
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    • v.1 no.1
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    • pp.131-140
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    • 1994
  • Box-Jenkins 시계열 분석에서 모형검진을 위한 통계량으로 잔차의 자기상관함수를 이용한 Box와 Pierce(1970)의 포트맨토우 검정과 Ljung과 Box(1978)의 변형된 포트맨토우 검정을 Basawa(1987)가 제안한 예측오차를 이용한 모형 검진 방법과 비교, 분석하였다. 시뮬레이션 연구를 수행하여 경험적 평균, 분산 및 유의 수준을 비교하여 과대적합의 방법을 이용하여 검정력을 비교하였다.

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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 and Independence Tests for Major 8 Companies of Korean Stock Market (한국 주식시장 상위 8개사에 대한 적합도 검정 및 독립성 검정)

  • Min, Seungsik
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1245-1255
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    • 2015
  • In this paper, we investigated the major 8 companies of Korean stock market, and carried out the goodness of fit and independence tests. We found out the distributions of absolute returns are closed to compressed exponential distribution. The parameters are dominant that 1 < ${\beta}$ < 2, followed by ${\beta}=1$(exponential distribution) and ${\beta}=2$(normal distribution). Meanwhile, we assured that most of the absolute returns for major 8 companies have relevance to each other by chi-square independence test.

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.

A goodness - of - fit test for the exponential distribution with unknown parameters (모수가 미지인 상황에서의 지수분포성 적합도 검정방법)

  • 김부용
    • The Korean Journal of Applied Statistics
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    • v.4 no.2
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    • pp.157-170
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    • 1991
  • This article is concerned with the goodness - of - fit test for exponentiality when both the scale and location parameters are unknown. A test procedure based on the $L_1$-norm of discrepancy between the cumulative distribution function and the empirical distribution function is proposed, and the critical values of the test statistic are obtained by Monte Carlo simulations. Also the null distributions of the proposed test statistic are presented for small sample sizes. The power of tests under certain alternative distributions is investigated to compare the proposed test statistic with the well-known EDF test statistics. Our Monte Carlo power studies reveal that the proposed test statistic has good power properties, for moderate-to-large sample sizes, in comparison to other statistics although it is a conservative test.

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