IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v95y2005i1p76-106.html
   My bibliography  Save this article

Block thresholding for density estimation: local and global adaptivity

Author

Listed:
  • Chicken, Eric
  • Cai, T. Tony

Abstract

We consider wavelet block thresholding method for density estimation. A block-thresholded density estimator is proposed and is shown to achieve optimal global rate of convergence over Besov spaces and simultaneously attain the optimal adaptive pointwise convergence rate as well. These results are obtained in part through the determination of an optimal block length.

Suggested Citation

  • Chicken, Eric & Cai, T. Tony, 2005. "Block thresholding for density estimation: local and global adaptivity," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 76-106, July.
  • Handle: RePEc:eee:jmvana:v:95:y:2005:i:1:p:76-106
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(04)00156-3
    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. Efromovich, Sam, 1994. "On adaptive estimation of nonlinear functionals," Statistics & Probability Letters, Elsevier, vol. 19(1), pages 57-63, January.
    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. Bulla, Ingo & Chesneau, Christophe & Navarro, Fabien & Mark, Tanya, 2015. "A note on the adaptive estimation of a bi-dimensional density in the case of knowledge of the copula density," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 6-13.
    2. Renyu Ye & Xinsheng Liu & Yuncai Yu, 2020. "Pointwise Optimality of Wavelet Density Estimation for Negatively Associated Biased Sample," Mathematics, MDPI, vol. 8(2), pages 1-12, February.
    3. Karol Dziedziul & Magdalena Kucharska & Barbara Wolnik, 2011. "Estimation of the smoothness of density," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 991-1001.
    4. Krebs, Johannes T.N., 2018. "Nonparametric density estimation for spatial data with wavelets," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 300-319.
    5. Steigerwald, Douglas G, 2006. "A Note on Adaptive Estimation," University of California at Santa Barbara, Economics Working Paper Series qt94v9g27p, Department of Economics, UC Santa Barbara.
    6. Li, Linyuan, 2008. "On the block thresholding wavelet estimators with censored data," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1518-1543, September.
    7. 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.
    8. Chen, Di-Rong & Cheng, Kun & Liu, Chao, 2022. "Framelet block thresholding estimator for sparse functional data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    9. Efromovich, Sam, 2011. "Nonparametric estimation of the anisotropic probability density of mixed variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 468-481, March.
    10. Li, Linyuan, 2015. "Nonparametric adaptive density estimation on random fields using wavelet method," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 346-355.

    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. Tony Cai, T. & Low, Mark G., 2006. "Adaptation under probabilistic error for estimating linear functionals," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 231-245, January.

    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:95:y:2005:i:1:p:76-106. 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.