IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i4p1132-1141.html
   My bibliography  Save this article

New goodness-of-fit tests based on fiducial empirical distribution function

Author

Listed:
  • Xu, Xingzhong
  • Ding, Xiaobo
  • Zhao, Shuran

Abstract

In this paper we derive new tests for goodness of fit based on the fiducial empirical distribution function (EDF) after the probability integral transformation of the sample. Note that the fiducial EDF for a set of given sample observations is a randomized distribution function. By substituting the fiducial EDF for the classical EDF in the Kolmogorov-Smirnov, Cramér-von Mises statistics and so forth, randomized statistics are derived, of which the qth quantile and the expectation are chosen as test statistics. It emerges from Monte Carlo simulations that in most cases there exist some of the new tests having better power properties than the corresponding tests based on the classical EDF and Pyke's modified EDF.

Suggested Citation

  • Xu, Xingzhong & Ding, Xiaobo & Zhao, Shuran, 2009. "New goodness-of-fit tests based on fiducial empirical distribution function," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1132-1141, February.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:1132-1141
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00482-9
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jin Zhang, 2002. "Powerful goodness‐of‐fit tests based on the likelihood ratio," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 281-294, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daojiang He & Xingzhong Xu, 2013. "A goodness-of-fit testing approach for normality based on the posterior predictive distribution," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 1-18, March.
    2. T. Fischer & U. Kamps, 2013. "Power maps in goodness-of-fit testing," Computational Statistics, Springer, vol. 28(3), pages 1365-1382, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vexler, Albert & Gurevich, Gregory, 2010. "Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 531-545, February.
    2. L. Ndwandwe & J. S. Allison & L. Santana & I. J. H. Visagie, 2023. "Testing for the Pareto type I distribution: a comparative study," METRON, Springer;Sapienza Università di Roma, vol. 81(2), pages 215-256, August.
    3. Zhang, Jin & Wu, Yuehua, 2007. "k-Sample tests based on the likelihood ratio," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4682-4691, May.
    4. J. I. Beltrán-Beltrán & F. J. O’Reilly, 2019. "On goodness of fit tests for the Poisson, negative binomial and binomial distributions," Statistical Papers, Springer, vol. 60(1), pages 1-18, February.
    5. Jesse Frey, 2008. "An exact distribution-free one-sample test for equivalence," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 739-750.
    6. Coin, Daniele, 2008. "A goodness-of-fit test for normality based on polynomial regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2185-2198, January.
    7. J. S. Allison & L. Santana & N. Smit & I. J. H. Visagie, 2017. "An ‘apples to apples’ comparison of various tests for exponentiality," Computational Statistics, Springer, vol. 32(4), pages 1241-1283, December.
    8. Lykou, R. & Tsaklidis, G. & Papadimitriou, E., 2020. "Change point analysis on the Corinth Gulf (Greece) seismicity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    9. M. Cockeran & S. G. Meintanis & L. Santana & J. S. Allison, 2021. "Goodness-of-fit testing of survival models in the presence of Type–II right censoring," Computational Statistics, Springer, vol. 36(2), pages 977-1010, June.
    10. Wolfgang Rolke & Cristian Gutierrez Gongora, 2021. "A chi-square goodness-of-fit test for continuous distributions against a known alternative," Computational Statistics, Springer, vol. 36(3), pages 1885-1900, September.
    11. Zhang, Jin & Wu, Yuehua, 2005. "Likelihood-ratio tests for normality," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 709-721, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:1132-1141. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.