IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v42y1999i2p175-184.html
   My bibliography  Save this article

Limiting behavior of the ICF test for normality under Gram-Charlier alternatives

Author

Listed:
  • Epps, T. W.

Abstract

The integrated characteristic function (ICF) test, introduced by Epps and Pulley (1983, Biometrika 70, 723-726) and Baringhaus and Henze (1988, Metrika 35, 339-348), has become recognized as a powerful omnibus test for univariate and multivariate normality. Although the test statistic is of simple closed form, it is derived as a weighted integral of the squared modulus of the difference between the c.f.s of the standardized sample and the spherical normal. The canonical weight function depends on an arbitrary smoothing parameter that the user must specify. We derive here an approximate lower bound for the power of the ICF test when the data are from a distribution represented as a finite Gram-Charlier expansion. The result sheds light on how the test's power depends on the smoothing parameter and the characteristics of the data.

Suggested Citation

  • Epps, T. W., 1999. "Limiting behavior of the ICF test for normality under Gram-Charlier alternatives," Statistics & Probability Letters, Elsevier, vol. 42(2), pages 175-184, April.
    • Handle: RePEc:eee:stapro:v:42:y:1999:i:2:p:175-184
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(98)00207-7
    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. N. Henze, 1990. "An approximation to the limit distribution of the epps-pulley test statistic for normality," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 37(1), pages 7-18, December.
    2. Henze, Norbert & Wagner, Thorsten, 1997. "A New Approach to the BHEP Tests for Multivariate Normality," Journal of Multivariate Analysis, Elsevier, vol. 62(1), pages 1-23, July.
    3. L. Baringhaus & N. Henze, 1988. "A consistent test for multivariate normality based on the empirical characteristic function," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 35(1), pages 339-348, December.
    4. Sándor Csörgő, 1989. "Consistency of some tests for multivariate normality," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 36(1), pages 107-116, December.
    5. Henze, Norbert, 1997. "Extreme smoothing and testing for multivariate normality," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 203-213, October.
    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. Wanfang Chen & Marc G. Genton, 2023. "Are You All Normal? It Depends!," International Statistical Review, International Statistical Institute, vol. 91(1), pages 114-139, April.
    2. Jiménez Gamero, M.D. & Muñoz García, J. & Pino Mejías, R., 2005. "Testing goodness of fit for the distribution of errors in multivariate linear models," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 301-322, August.
    3. J. S. Allison & M. Hušková & S. G. Meintanis, 2018. "Testing the adequacy of semiparametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 70-94, March.
    4. Max Wornowizki & Roland Fried & Simos G. Meintanis, 2017. "Fourier methods for analyzing piecewise constant volatilities," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(3), pages 289-308, July.
    5. Meintanis, Simos G. & Ngatchou-Wandji, Joseph & Taufer, Emanuele, 2015. "Goodness-of-fit tests for multivariate stable distributions based on the empirical characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 171-192.
    6. Norbert Henze, 2002. "Invariant tests for multivariate normality: a critical review," Statistical Papers, Springer, vol. 43(4), pages 467-506, October.
    7. Jiménez-Gamero, M.D. & Alba-Fernández, V. & Muñoz-García, J. & Chalco-Cano, Y., 2009. "Goodness-of-fit tests based on empirical characteristic functions," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3957-3971, October.
    8. Leucht, Anne & Neumann, Michael H., 2009. "Consistency of general bootstrap methods for degenerate U-type and V-type statistics," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1622-1633, September.
    9. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos Meintanis, 2012. "Monitoring changes in the error distribution of autoregressive models based on Fourier methods," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(4), pages 605-634, December.
    10. Klar, Bernhard & Meintanis, Simos G., 2005. "Tests for normal mixtures based on the empirical characteristic function," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 227-242, April.

    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. Norbert Henze, 2002. "Invariant tests for multivariate normality: a critical review," Statistical Papers, Springer, vol. 43(4), pages 467-506, October.
    2. Wanfang Chen & Marc G. Genton, 2023. "Are You All Normal? It Depends!," International Statistical Review, International Statistical Institute, vol. 91(1), pages 114-139, April.
    3. Philip Dörr & Bruno Ebner & Norbert Henze, 2021. "Testing multivariate normality by zeros of the harmonic oscillator in characteristic function spaces," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 456-501, June.
    4. Tenreiro, Carlos, 2011. "An affine invariant multiple test procedure for assessing multivariate normality," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1980-1992, May.
    5. Tenreiro, Carlos, 2009. "On the choice of the smoothing parameter for the BHEP goodness-of-fit test," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1038-1053, February.
    6. Norbert Henze & María Dolores Jiménez-Gamero, 2019. "A new class of tests for multinormality with i.i.d. and garch data based on the empirical moment generating function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 499-521, June.
    7. Bruno Ebner & Norbert Henze, 2020. "Tests for multivariate normality—a critical review with emphasis on weighted $$L^2$$ L 2 -statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 845-892, December.
    8. L. Baringhaus & B. Ebner & N. Henze, 2017. "The limit distribution of weighted $$L^2$$ L 2 -goodness-of-fit statistics under fixed alternatives, with applications," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(5), pages 969-995, October.
    9. Bruno Ebner & Norbert Henze, 2023. "On the eigenvalues associated with the limit null distribution of the Epps-Pulley test of normality," Statistical Papers, Springer, vol. 64(3), pages 739-752, June.
    10. Henze, Norbert & Wagner, Thorsten, 1997. "A New Approach to the BHEP Tests for Multivariate Normality," Journal of Multivariate Analysis, Elsevier, vol. 62(1), pages 1-23, July.
    11. Steffen Betsch & Bruno Ebner, 2020. "Testing normality via a distributional fixed point property in the Stein characterization," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 105-138, March.
    12. Chen, Feifei & Jiménez–Gamero, M. Dolores & Meintanis, Simos & Zhu, Lixing, 2022. "A general Monte Carlo method for multivariate goodness–of–fit testing applied to elliptical families," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    13. Meintanis, S. & Ushakov, N. G., 2004. "Binned goodness-of-fit tests based on the empirical characteristic function," Statistics & Probability Letters, Elsevier, vol. 69(3), pages 305-314, September.
    14. Norbert Henze & Celeste Mayer, 2020. "More good news on the HKM test for multivariate reflected symmetry about an unknown centre," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 741-770, June.
    15. A. Cabaña & E. M. Cabaña, 2003. "Tests of Normality Based on Transformed Empirical Processes," Methodology and Computing in Applied Probability, Springer, vol. 5(3), pages 309-335, September.
    16. Henze, N. & Klar, B. & Meintanis, S. G., 2003. "Invariant tests for symmetry about an unspecified point based on the empirical characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 87(2), pages 275-297, November.
    17. Leucht, Anne & Neumann, Michael H., 2009. "Consistency of general bootstrap methods for degenerate U-type and V-type statistics," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1622-1633, September.
    18. Gutjahr, Steffen & Henze, Norbert & Folkers, Martin, 1999. "Shortcomings of Generalized Affine Invariant Skewness Measures," Journal of Multivariate Analysis, Elsevier, vol. 71(1), pages 1-23, October.
    19. Christian Goldmann & Bernhard Klar & Simos Meintanis, 2015. "Data transformations and goodness-of-fit tests for type-II right censored samples," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(1), pages 59-83, January.
    20. Simos G. Meintanis & James Allison & Leonard Santana, 2016. "Goodness-of-fit tests for semiparametric and parametric hypotheses based on the probability weighted empirical characteristic function," Statistical Papers, Springer, vol. 57(4), pages 957-976, December.

    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:stapro:v:42:y:1999:i:2:p:175-184. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.