The bivariate Power-Normal and the bivariate Johnson’s System bounded distribution in forestry, including height curves. Supplementary material.

Content Provider	Semantic Scholar
Author	Mønness, Erik
Copyright Year	2014
Abstract	A bivariate 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 powernormal is a good candidate model for use in forest stands.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://brage.bibsys.no/xmlui/bitstream/handle/11250/298119/BivariateMonness.pdf?isAllowed=y&sequence=1
Alternate Webpage(s)	https://brage.bibsys.no/xmlui/bitstream/handle/11250/227881/Rapport09_14.pdf?isAllowed=y&sequence=3
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article