%0 Research article
%T The use of quantile trees in the prediction of the diameter distribution of a stand
%A Mehtätalo, Lauri
%A Maltamo, Matti
%A Kangas, Annika
%D 2006
%J Silva Fennica
%V 40
%N 3
%R doi:10.14214/sf.333
%U https://silvafennica.fi/article/333
%X 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.