Current issue: 55(2)

Under compilation: 55(3)

Scopus CiteScore 2019: 3.1
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Silva Fennica 1926-1997
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1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles containing the keyword 'order statistics'.

Category: Research article

article id 333, category Research article
Lauri Mehtätalo, Matti Maltamo, Annika Kangas. (2006). The use of quantile trees in the prediction of the diameter distribution of a stand. Silva Fennica vol. 40 no. 3 article id 333. https://doi.org/10.14214/sf.333
This study deals with the prediction of the basal area diameter distribution of a stand without using a complete sample of diameters from the target stand. Traditionally, this problem has been solved by either the parameter recovery method or the parameter prediction method. This study uses the parameter prediction method and the percentile based diameter distribution with a recent development that makes it possible to improve these predictions by using sample order statistics. A sample order statistic is a tree whose diameter and rank at the plot are known, and is referred to in this paper as a quantile tree. This study tested 13 different strategies for selection of the quantile trees from among the trees of horizontal point sample plots, and compared them with respect to RMSE and the bias of four criterion variables in a dataset of 512 stands. The sample minimum was found to be the most promising alternative with respect to RMSE, even though it introduced a rather large amount of bias in the criterion variables. Other good and less biased alternatives are the second and third smallest trees and the tree closest to the plot centre. The use of minimum is recommended for practical inventories because its rank is probably easiest to determine correctly in the field.
  • Mehtätalo, Yale School of Forestry and Environmental Studies, 205 Prospect Street, New Haven, CT 06511, USA ORCID ID:E-mail: lauri.mehtatalo@metla.fi (email)
  • Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Kangas, University of Helsinki, Department of Forest Resources Management, P.O.Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:

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