IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v57y2013i1p59-67.html
   My bibliography  Save this article

A maximum entropy type test of fit: Composite hypothesis case

Author

Listed:
  • Lee, Sangyeol

Abstract

In this paper, we propose a goodness of fit test based on maximum entropy. As an extension of the result on the simple versus simple hypothesis case handled by Lee et al. (2011), a composite hypothesis case is taken into consideration. To eliminate the parameter estimation effect, we apply the Khmaladze transformation for the empirical process and obtain the asymptotic distribution of the proposed test. The performance of the test is investigated through Monte Carlo simulations.

Suggested Citation

  • Lee, Sangyeol, 2013. "A maximum entropy type test of fit: Composite hypothesis case," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 59-67.
  • Handle: RePEc:eee:csdana:v:57:y:2013:i:1:p:59-67
    DOI: 10.1016/j.csda.2012.06.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312002460
    Download Restriction: Full text for ScienceDirect subscribers only.

    File URL: https://libkey.io/10.1016/j.csda.2012.06.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Sangyeol Lee & Okyoung Na & Seongryong Na, 2003. "On the cusum of squares test for variance change in nonstationary and nonparametric time series models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(3), pages 467-485, September.
    2. Sangyeol Lee & Jeongcheol Ha & Okyoung Na & Seongryong Na, 2003. "The Cusum Test for Parameter Change in Time Series Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 781-796, December.
    3. Jushan Bai, 2003. "Testing Parametric Conditional Distributions of Dynamic Models," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 531-549, August.
    4. Bera, Anil K. & Jarque, Carlos M., 1981. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals : Monte Carlo Evidence," Economics Letters, Elsevier, vol. 7(4), pages 313-318.
    5. Lee, Sangyeol & Vonta, Ilia & Karagrigoriou, Alex, 2011. "A maximum entropy type test of fit," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2635-2643, September.
    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. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.

    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. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    2. Maria Mohr & Natalie Neumeyer, 2021. "Nonparametric volatility change detection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 529-548, June.
    3. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
    4. Koichi Maekawa & Sangyeol & Lee, 2004. "The Cusum Test for Parameter Change in Regression with ARCH Errors," Econometric Society 2004 Far Eastern Meetings 606, Econometric Society.
    5. Vanessa Berenguer-Rico & Bent Nielsen, 2015. "Cumulated sum of squares statistics for non-linear and non-stationary regressions," Economics Papers 2015-W09, Economics Group, Nuffield College, University of Oxford.
    6. Josephine Njeri Ngure & Anthony Gichuhi Waititu, 2021. "Consistency of an Estimator for Change Point in Volatility of Financial Returns," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 13(1), pages 1-56, February.
    7. Kim, Byungsoo, 2018. "Robust maximum entropy test for GARCH models based on a minimum density power divergence estimator," Economics Letters, Elsevier, vol. 162(C), pages 93-97.
    8. Marco Barassi & Lajos Horváth & Yuqian Zhao, 2020. "Change‐Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 340-349, April.
    9. Lee, Sangyeol, 2014. "Goodness of fit test for discrete random variables," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 92-100.
    10. Lee, Taewook, 2013. "On Jarque–Bera normality and cusum parameter change tests for BCTT-GARCH models," Economics Letters, Elsevier, vol. 119(1), pages 50-54.
    11. Na, Okyoung & Lee, Sangyeol, 2007. "Moving estimates test with time varying bandwidth," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1356-1375, August.
    12. Badagian Baharian, Ana Laura & Kaiser Remiro, Regina & Peña, Daniel, 2013. "The change-point problem and segmentation of processes with conditional heteroskedasticity," DES - Working Papers. Statistics and Econometrics. WS ws131718, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Thomas Gkelsinis & Alex Karagrigoriou, 2020. "Theoretical Aspects on Measures of Directed Information with Simulations," Mathematics, MDPI, vol. 8(4), pages 1-13, April.
    14. Juan Carlos Escanciano & Zaichao Du, 2015. "Backtesting Expected Shortfall: Accounting for Tail Risk," CAEPR Working Papers 2015-001, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    15. Juan Mora & Antonia Febrer, 2005. "Wage Distribution In Spain, 1994-1999: An Application Of A Flexible Estimator Of Conditional Distributions," Working Papers. Serie EC 2005-04, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    16. Corradi, Valentina & Swanson, Norman R., 2004. "A test for the distributional comparison of simulated and historical data," Economics Letters, Elsevier, vol. 85(2), pages 185-193, November.
    17. Magdalena Mikolajek-Gocejna, 2021. "Estimation, Instability, and Non-Stationarity of Beta Coefficients for Twenty-four Emerging Markets in 2005-2021," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 370-395.
    18. Marc Lavoie & Gabriel Rodriguez & Mario Seccareccia, 2004. "Similitudes and Discrepancies in Post-Keynesian and Marxist Theories of Investment: A Theoretical and Empirical Investigation," International Review of Applied Economics, Taylor & Francis Journals, vol. 18(2), pages 127-149.
    19. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    20. Lajos Horvath & Lorenzo Trapani, 2021. "Changepoint detection in random coefficient autoregressive models," Papers 2104.13440, arXiv.org.

    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:57:y:2013:i:1:p:59-67. 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.