IDEAS home Printed from https://ideas.repec.org/a/caa/jnljfs/v60y2014i11id56-2014-jfs.html
   My bibliography  Save this article

Use of nonparametric regression methods for developing a local stem form model

Author

Listed:
  • K. Kuželka

    (Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic)

  • R. Marušák

    (Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic)

Abstract

A local mean stem curve of spruce was represented using regression splines. Abilities of smoothing spline and P-spline to model the mean stem curve were evaluated using data of 85 carefully measured stems of Norway spruce. For both techniques the optimal amount of smoothing was investigated in dependence on the number of training stems using a cross-validation method. Representatives of main groups of parametric models - single models, segmented models and models with variable coefficient - were compared with spline models using five statistic criteria. Both regression splines performed comparably or better as all representatives of parametric models independently of the numbers of stems used as training data.

Suggested Citation

  • K. Kuželka & R. Marušák, 2014. "Use of nonparametric regression methods for developing a local stem form model," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 60(11), pages 464-471.
    • Handle: RePEc:caa:jnljfs:v:60:y:2014:i:11:id:56-2014-jfs
    DOI: 10.17221/56/2014-JFS
    as

    Download full text from publisher

    File URL: http://jfs.agriculturejournals.cz/doi/10.17221/56/2014-JFS.html
    Download Restriction: free of charge
    File URL: http://jfs.agriculturejournals.cz/doi/10.17221/56/2014-JFS.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.17221/56/2014-JFS?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. T. Nummi & J. Mottonen, 2004. "Prediction of Stem Measurements of Scots Pine," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(1), pages 105-114.
    Full references (including those not matched with items on IDEAS)

    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.

      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:caa:jnljfs:v:60:y:2014:i:11:id:56-2014-jfs. 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: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

      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.