• Title/Summary/Keyword: Goodness of fit

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On the Goodness-of-fit Test in Regression Using the Difference Between Nonparametric and Parametric Fits

  • Hong, Chang-Kon;Joo, Jae-Seon
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.1-14
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    • 2001
  • This paper discusses choosing the weight function of the Hardle and Mammen statistic in nonparametric goodness-of-fit test for regression curve. For this purpose, we modify the Hardle and Mammen statistic and derive its asymptotic distribution. Some results on the test statistic from the wild bootstrapped sample are also obtained. Through Monte Carlo experiment, we check the validity of these results. Finally, we study the powers of the test and compare with those of the Hardle and Mammen test through the simulation.

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Goodness-of-Fit Test for the Pareto Distribution Based on the Transformed Sample Lorenz curve

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.113-119
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    • 2002
  • A powerful and easily computed goodness-of-fit test for Pareto distribution which does not depend on the unknown location and scale parameters is proposed based on the transformed sample Lorenz curve. We compare the power of the proposed test statistic with the other goodness-of-fit tests for Pareto distribution against various alternatives through Monte Carlo methods.

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ON THE GOODNESS OF FIT TEST FOR DISCRETELY OBSERVED SAMPLE FROM DIFFUSION PROCESSES: DIVERGENCE MEASURE APPROACH

  • Lee, Sang-Yeol
    • Journal of the Korean Mathematical Society
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    • v.47 no.6
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    • pp.1137-1146
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    • 2010
  • In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.

Goodness-of-Fit Test for the Exponential Distribution Based on the Transformed Sample Lorenz curve

  • Suk-Bok;Young-Suk
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.277-284
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    • 2000
  • The transformed sample Lorenz curve provides a powerful and easily computed goodness-of-fit test for exponentiality which does not depend on the unknown scale parameter. We compare the power of the transformed sample Lorenz curve statistic with the other goodness-of-fit tests for exponentiality against various alternatives through Monte Carlo methods and discuss the results.

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A Goodness of Fit Approach to Testing Exponential Better than Used (EBU) Life Distributions

  • Abu-Youssef, S.E.
    • International Journal of Reliability and Applications
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    • v.9 no.1
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    • pp.71-78
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    • 2008
  • Based on the goodness of fit approach, a new test is presented for testing exponentiality versus exponential better (worse) than used (EBU (EWU)) class of life distributions. The new test is much simpler to compute, asymptotically normal, enjoys good power and performs better than previous tests in terms of power and Pitman asymptotic efficiencies for several alternatives.

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ENTROPY-BASED GOODNESS OF FIT TEST FOR A COMPOSITE HYPOTHESIS

  • Lee, Sangyeol
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.2
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    • pp.351-363
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    • 2016
  • In this paper, we consider the entropy-based goodness of fit test (Vasicek's test) for a composite hypothesis. The test measures the discrepancy between the nonparametric entropy estimate and the parametric entropy estimate obtained from an assumed parametric family of distributions. It is shown that the proposed test is asymptotically normal under regularity conditions, but is affected by parameter estimates. As a remedy, a bootstrap version of Vasicek's test is proposed. Simulation results are provided for illustration.

Minimum Hellinger Distance Bsed Goodness-of-fit Tests in Normal Models: Empirical Approach

  • Dong Bin Jeong
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.967-976
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    • 1999
  • In this paper we study the Hellinger distance based goodness-of-fit tests that are analogs of likelihood ratio tests. The minimum Hellinger distance estimator (MHDE) in normal models provides an excellent robust alternative to the usual maximum likelihood estimator. Our simulation results show that the Hellinger deviance test (Simpson 1989) based goodness-of-fit test is robust when data contain outliers. The proposed hellinger deviance test(Simpson 1989) is a more direcct method for obtaining robust inferences than an automated outlier screen method used before the likelihood ratio test data analysis.

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Goodness of Fit Tests of Cox's Proportional Hazards Model

  • Song, Hae-Hiang;Lee, Sun-Ho
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.379-402
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    • 1994
  • Graphical and numerical methods for checking the assumption of proportional hazards of Cox model for censored survival data are discussed. The strenths and weaknessess of several goodness of fit tests for the propotional hazards for the two-sample problem are evaluated with Monte Carlo simulations, and the tests of Schoenfeld (1980), Andersen (1982), Wei (1984), and Gill and Schumacher (1987) are considered. The goodness of fit methods are illustrated with the survival data of patients who had chronic liver disease and had been treated with the endoscopy injection sclerotheraphy. Two other examples of data known to have nonpropotional hazards are also used in the illustration.

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Comparison of Powers in Goodness of Fit Test of Quadratic Measurement Error Model

  • Moon, Myung-Sang
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.229-240
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    • 2002
  • Whether to use linear or quadratic model in the analysis of regression data is one of the important problems in classical regression model and measurement error model (MEM). In MEM, four goodness of fit test statistics are available In solving that problem. Two are from the derivation of estimators of quadratic MEM, and one is from that of the general $k^{th}$-order polynomial MEM. The fourth one is derived as a variation of goodness of fit test statistic used in linear MEM. The purpose of this paper is to find the most powerful test statistic among them through the small-scale simulation.

A Goodness of Fit Approach to Major Lifetesting Problems

  • Ahmad, Ibrahim A.;Alwasel, Ibrahim A.;Mugdadi, A.R.
    • International Journal of Reliability and Applications
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    • v.2 no.2
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    • pp.81-97
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    • 2001
  • Lifetesting problems have been the subject of investigations for over three decades. Most suggested approaches are markedly different from those used in the related but wider goodness of fit problems. In the current investigation, it is demonstrated that a goodness of fit approach is possible in many lifetesting problems and that It results in simpler procedures that are asymptotically equivalent or better than standard ones. They may also have superior finite sample behavior. Several perennial classes are addressed here. The class of increasing failure rate (IFR) and the class of new better than used (NBU) are addressed first. In addition, we provide testing for a newer and practical class of new better than used in convex ordering (NBUC) due to Cao and Wang (1991). Other classes can be developed similarly and this point is illustrated with the classes of new better than used in expectation (NBUE) and harmonic new better than used in expectation (HNBUE).

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