IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v16y1993i5p397-405.html
   My bibliography  Save this article

Data-dependent bandwidth choice for a grade density kernel estimate

Author

Listed:
  • Cwik, Jan
  • Mielniczuk, Jan

Abstract

The method of choosing a smoothing parameter for a grade density kernel estimate g is proposed. It consists in estimating the minimizer of the asymptotic MISE for two main terms in the expansion of g. The behaviour of the estimates incorporating proposed bandwidths is investigated in the variety of parametric models and compared with that of estimates using bandwidths suitable for the complete observability case. They are shown to perform well for unimodal densities and moderately well for multimodal ones.

Suggested Citation

  • Cwik, Jan & Mielniczuk, Jan, 1993. "Data-dependent bandwidth choice for a grade density kernel estimate," Statistics & Probability Letters, Elsevier, vol. 16(5), pages 397-405, April.
    • Handle: RePEc:eee:stapro:v:16:y:1993:i:5:p:397-405
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(93)90074-S
    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.

    Citations

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


    Cited by:

    1. Zoya Nissanov & Maria Grazia Pittau, 2016. "Measuring changes in the Russian middle class between 1992 and 2008: a nonparametric distributional analysis," Empirical Economics, Springer, vol. 50(2), pages 503-530, March.
    2. Gaëlle Chagny & Claire Lacour, 2015. "Optimal adaptive estimation of the relative density," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 605-631, September.
    3. Riccardo Massari, 2009. "Is income becoming more polarized Italy? A closer look with a distributional approach," Working Papers 1, Doctoral School of Economics, Sapienza University of Rome.
    4. Mnatsakanov, Robert M. & Pommeret, Denys, 2024. "On recovering the relative distribution, Part 1: The moment-recovered approach," Statistics & Probability Letters, Elsevier, vol. 208(C).
    5. Elisa–María Molanes-López & Ricardo Cao, 2008. "Relative density estimation for left truncated and right censored data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 693-720.
    6. Mark S. Handcock & Paul L. Janssen, 2002. "Statistical Inference for the Relative Density," Sociological Methods & Research, , vol. 30(3), pages 394-424, February.
    7. Cao, Ricardo & Janssen, Paul & Veraverbeke, Noel, 2001. "Relative density estimation and local bandwidth selection for censored data," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 497-510, June.

    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:16:y:1993:i:5:p:397-405. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.