IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v16y2001i1d10.1007_s001800100059.html
   My bibliography  Save this article

Presentation of smoothers: the family approach

Author

Listed:
  • J. S. Marron

    (University of North Carolina)

  • S. S. Chung

    (Chonbuk University)

Abstract

Summary The product of most statistical smoothing methods is a single curve estimate. A drawback of such methods is that what is learned varies with choice of the smoothing parameter. This paper proposes simultaneous display of all important features, through presentation of a family of smooths. Some suggestions are given as to how this should be done.

Suggested Citation

  • J. S. Marron & S. S. Chung, 2001. "Presentation of smoothers: the family approach," Computational Statistics, Springer, vol. 16(1), pages 195-207, March.
  • Handle: RePEc:spr:compst:v:16:y:2001:i:1:d:10.1007_s001800100059
    DOI: 10.1007/s001800100059
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s001800100059
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s001800100059?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. Park, B.U. & Turlach, B.A., 1992. "Rejoinder to ``Practical performance of several data driven bandwidth selectors"," LIDAM Reprints CORE 1022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. PARK, Byeong U. & TURLACH, Berwin A., 1992. "Practical performance of several data driven bandwidth selectors," LIDAM Reprints CORE 1001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Park, B. & Turlach, B., 1992. "Practical Performance of Several Data Driven Bandwidih Selectors," Papers 9203, Catholique de Louvain - Institut de statistique.
    4. Kooperberg, Charles & Stone, Charles J., 1991. "A study of logspline density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 12(3), pages 327-347, November.
    5. J. S. Marron & Frederic Udina, 1995. "Interactive local bandwidth choice," Economics Working Papers 109, Department of Economics and Business, Universitat Pompeu Fabra.
    6. PARK, Byeong & TURLACH, Berwin, 1992. "Practical performance of several data driven bandwidth selectors," LIDAM Discussion Papers CORE 1992005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Peter Diggle, 1985. "A Kernel Method for Smoothing Point Process Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(2), pages 138-147, June.
    8. Cao, Ricardo & Cuevas, Antonio & Gonzalez Manteiga, Wensceslao, 1994. "A comparative study of several smoothing methods in density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 17(2), pages 153-176, February.
    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. Lasse Holmström & Leena Pasanen, 2017. "Statistical Scale Space Methods," International Statistical Review, International Statistical Institute, vol. 85(1), pages 1-30, April.
    2. Răileanu-Szeles, Monica & Albu, Lucian, 2015. "Nonlinearities and divergences in the process of European financial integration," Economic Modelling, Elsevier, vol. 46(C), pages 416-425.

    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. Wen-Ching Wang, 2018. "Setting up evaluate indicators for slope control engineering based on spatial clustering analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 921-939, September.
    2. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    3. Robert J. R. Elliott & Liza Jabbour & Liyun Zhang, 2016. "Firm productivity and importing: Evidence from Chinese manufacturing firms," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(3), pages 1086-1124, August.
    4. Seok-Oh Jeong & Byeong Park & Léopold Simar, 2010. "Nonparametric conditional efficiency measures: asymptotic properties," Annals of Operations Research, Springer, vol. 173(1), pages 105-122, January.
    5. Jos'e E. Figueroa-L'opez & Cheng Li, 2016. "Optimal Kernel Estimation of Spot Volatility of Stochastic Differential Equations," Papers 1612.04507, arXiv.org.
    6. Tortosa-Ausina, Emili, 2002. "Exploring efficiency differences over time in the Spanish banking industry," European Journal of Operational Research, Elsevier, vol. 139(3), pages 643-664, June.
    7. Declan Curran & Michael Funke & Jue Wang, 2007. "Economic Growth across Space and Time: subprovincial Evidence from Mainland China," Quantitative Macroeconomics Working Papers 20710, Hamburg University, Department of Economics.
    8. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
    9. Duc Devroye & J. Beirlant & R. Cao & R. Fraiman & P. Hall & M. Jones & Gábor Lugosi & E. Mammen & J. Marron & C. Sánchez-Sellero & J. Uña & F. Udina & L. Devroye, 1997. "Universal smoothing factor selection in density estimation: theory and practice," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(2), pages 223-320, December.
    10. Emili Tortosa-Ausina, 2000. "Inefficient banks or inefficient assets," Working Papers 0005, Departament Empresa, Universitat Autònoma de Barcelona, revised Dec 2000.
    11. repec:zbw:bofitp:2007_021 is not listed on IDEAS
    12. Farmen, Mark & Marron, J. S., 1999. "An assessment of finite sample performance of adaptive methods in density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 143-168, April.
    13. Berwin A. TURLACH, "undated". "Bandwidth selection in kernel density estimation: a rewiew," Statistic und Oekonometrie 9307, Humboldt Universitaet Berlin.
    14. Emili Tortosa-Ausina, 2003. "Bank cost efficiency as distribution dynamics: controlling for specialization is important," Investigaciones Economicas, Fundación SEPI, vol. 27(1), pages 71-96, January.
    15. Cwik, J. & Koronacki, J., 1997. "A combined adaptive-mixtures/plug-in estimator of multivariate probability densities," Computational Statistics & Data Analysis, Elsevier, vol. 26(2), pages 199-218, December.
    16. Teruko Takada, 2001. "Nonparametric density estimation: A comparative study," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-10.
    17. Emili Tortosa Ausina, 1999. "-Convergence In Efficiency Of The Spanish Banking Firms As Distribution Dynamics," Working Papers. Serie EC 1999-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    18. Declan Curran & Michael Funke & Jue Wang, 2007. "Economic Growth across Space and Time: subprovincial Evidence from Mainland China," Quantitative Macroeconomics Working Papers 20710, Hamburg University, Department of Economics.
    19. Corak, Miles & Lauzon, Darren, 2009. "Differences in the distribution of high school achievement: The role of class-size and time-in-term," Economics of Education Review, Elsevier, vol. 28(2), pages 189-198, April.
    20. M. M. Salinas-Jimenez, 2003. "Technological change, efficiency gains and capital accumulation in labour productivity growth and convergence: an application to the Spanish regions," Applied Economics, Taylor & Francis Journals, vol. 35(17), pages 1839-1851.
    21. Marco BIANCHI, "undated". "A simple and fast method of regime shifts detection based on kernel density estimation," Statistic und Oekonometrie 9316, Humboldt Universitaet Berlin.

    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:spr:compst:v:16:y:2001:i:1:d:10.1007_s001800100059. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.