An approach to modeling the joint distribution of tree diameter and height data

作者：Ogana F N^*; Osho J S A; Gorgoso Varela J J

来源：Journal of Sustainable Forestry, 2018, 37(5): 475-488.

DOI：10.1080/10549811.2017.1422434

• Bivariate logit-logistic-dagum
• bivariate logit-logistic
• Johnson's S-BB
• bivariate kumaraswamybivariate burr distributions

Advantages of the application of bivariate distribution models to forest management cannot be overemphasized. However, there are quite a number of flexible statistical distributions not yet evaluated in their bivariate domains. Therefore, in this article, we evaluated the bivariate forms of some probability distribution models used in quantitative forestry. Six bivariate distributions were assessed: Burr XII (Burr XII-2), Dagum (Dagum-2), Kumaraswamy (Kum-2), the new Logit-Logistic-Dagum (LLD-2) distribution, Logit-Logistic (LL-2), and the much used Johnson's S-BB. All models were constructed using the Plackett's method except for the S-BB distribution. Appropriate constraints were imposed on the boundary parameters of the bivariate distributions using fractions derived from the Gumbel distribution. Models were fitted with maximum likelihood to the joint distribution of diameter and height data of Eucalyptus camaldulensis Dehn from 90 sample plots. Model assessment was based on negative log-likelihood (-Lambda Lambda), Corrected Akaike Information Criterion (AlCc), Bayesian Information Criterion (BIC) and Hannan-Quinn Criterion (HQC). The result showed that the Johnson's S-BB had the overall best performance. Their ranking order was: S-BB > LLD-2 > Burr XII-2 > Dagum-2 > LL-2 > Kum-2. These models can be used to simulate timber harvesting regime.

• 出版日期2018