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dc.contributor.authorMønness, Erik Neslein
dc.description.abstractbivariate diameter and height distribution yields a unified model of a forest stand. The bivariate Johnson’s System bounded distribution and the bivariate power-normal distribution are explored. The power-normal originates from the well-known Box-Cox transformation. As evaluated by the bivariate Kolmogorov-Smirnov distance, the bivariate power-normal distribution seems to be superior to the bivariate Johnson’s System bounded distribution. The conditional median height given the diameter is a possible height curve and is compared with a simple hyperbolic height curve. Evaluated by the height deviance, the hyperbolic function yields the best height prediction. A close second is the curve generated by a bivariate power-normal distribution. Johnson’s System bounded distributions suffer from the sigmoid shape of the association between height and diameter. The bivariate power-normal is easy to estimate with good numerical properties. The bivariate power-normal is a good candidate model for use in forest stands.nb_NO
dc.relation.ispartofseriesCanadian Journal of Forest Research;45(3)2015
dc.relation.haspartLenke til supplerende data:
dc.rightsNavngivelse-Ikkekommersiell-DelPåSammeVilkår 3.0 Norge*
dc.subjectbivariate Johnson’s System bounded distributionnb_NO
dc.subjectbivariate power-normal distributionnb_NO
dc.subjectheight curvenb_NO
dc.subjectBox-Cox transformationnb_NO
dc.titleThe bivariate Power-Normal and the bivariate Johnson’s System bounded distribution in forestry, including height curvesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.subject.nsiVDP::Agriculture and fishery disciplines: 900::Agriculture disciplines: 910::Forestry: 915nb_NO

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Navngivelse-Ikkekommersiell-DelPåSammeVilkår 3.0 Norge
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