IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v80y2002i2p256-284.html
   My bibliography  Save this article

Wavelet Threshold Estimation of a Regression Function with Random Design

Author

Listed:
  • Zhang, Shuanglin
  • Wong, Man-Yu
  • Zheng, Zhongguo

Abstract

The wavelet threshold estimator of a regression function for the random design is constructed. The optimal uniform convergence rate of the estimator in a ball of Besov Space Bsp, q is proved under general assumptions. The adaptive wavelet threshold estimator with near-optimal convergence rate in a wide range of Besov scale is also constructed.

Suggested Citation

  • Zhang, Shuanglin & Wong, Man-Yu & Zheng, Zhongguo, 2002. "Wavelet Threshold Estimation of a Regression Function with Random Design," Journal of Multivariate Analysis, Elsevier, vol. 80(2), pages 256-284, February.
  • Handle: RePEc:eee:jmvana:v:80:y:2002:i:2:p:256-284
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(00)91980-8
    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. Iain M. Johnstone & Bernard W. Silverman, 1997. "Wavelet Threshold Estimators for Data with Correlated Noise," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(2), pages 319-351.
    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. Michael Levine, 2019. "Robust functional estimation in the multivariate partial linear model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 743-770, August.

    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. Wishart, Justin Rory, 2011. "Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1871-1875.
    2. Linyuan Li & Yimin Xiao, 2007. "Mean Integrated Squared Error of Nonlinear Wavelet-based Estimators with Long Memory Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 299-324, June.
    3. Luan, Yihui & Xie, Zhongjie, 2001. "The wavelet identification for jump points of derivative in regression model," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 167-180, June.
    4. McGinnity, K. & Varbanov, R. & Chicken, E., 2017. "Cross-validated wavelet block thresholding for non-Gaussian errors," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 127-137.
    5. Fryzlewicz, Piotr & Nason, Guy P., 2004. "Smoothing the wavelet periodogram using the Haar-Fisz transform," LSE Research Online Documents on Economics 25231, London School of Economics and Political Science, LSE Library.
    6. repec:jss:jstsof:12:i08 is not listed on IDEAS
    7. Beran, Jan & Heiler, Mark A., 2008. "A nonparametric regression cross spectrum for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 684-714, April.
    8. Porto, Rogério F. & Morettin, Pedro A. & Aubin, Elisete C.Q., 2008. "Wavelet regression with correlated errors on a piecewise Hölder class," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2739-2743, November.
    9. Capobianco Enrico & Marras Elisabetta & Travaglione Antonella, 2011. "Multiscale Characterization of Signaling Network Dynamics through Features," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-32, November.
    10. Iolanda Lo Cascio, 2007. "Wavelet Analysis and Denoising: New Tools for Economists," Working Papers 600, Queen Mary University of London, School of Economics and Finance.
    11. Capobianco, Enrico, 2003. "Independent Multiresolution Component Analysis and Matching Pursuit," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 385-402, March.
    12. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    13. Graham Horgan, 1999. "Using wavelets for data smoothing: A simulation study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 923-932.
    14. Serban, Nicoleta, 2010. "Noise reduction for enhanced component identification in multi-dimensional biomolecular NMR studies," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1051-1065, April.
    15. Marcelo M. Taddeo & Pedro A. Morettin, 2023. "Bayesian P-Splines Applied to Semiparametric Models with Errors Following a Scale Mixture of Normals," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1331-1355, August.
    16. Salcedo, Gladys E. & Porto, Rogério F. & Morettin, Pedro A., 2012. "Comparing non-stationary and irregularly spaced time series," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3921-3934.
    17. Christophe Chesneau & Fabien Navarro, 2017. "On the pointwise mean squared error of a multidimensional term-by-term thresholding wavelet estimator," Working Papers 2017-68, Center for Research in Economics and Statistics.
    18. Capobianco, Enrico, 2004. "Effective decorrelation and space dimensionality reduction of multiscaling volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 340-346.
    19. Oleg Shestakov, 2020. "Wavelet Thresholding Risk Estimate for the Model with Random Samples and Correlated Noise," Mathematics, MDPI, vol. 8(3), pages 1-8, March.
    20. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
    21. Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.

    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:jmvana:v:80:y:2002:i:2:p:256-284. 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.