Management of marketable products of private plantations will not be sustainable without class girth being identifiable readily. Modeling marketable products is a key to obtain good fitness between observed and theore...Management of marketable products of private plantations will not be sustainable without class girth being identifiable readily. Modeling marketable products is a key to obtain good fitness between observed and theoretical girth distribution. We determine the best parameter recovery method with the Weibull function for two sylvicultural regimes (coppice and high forest). Data on stand variables were collected from 1101 sample plots. The three Weibull function parameters were estimated with three parameters recovery methods: the maximum likelihood method, the method of moments and the method of percentiles. Stepwise regression and the simultaneously re-estimated parameter using the Seemingly Unrelated Regression Estimation were applied to model each parameter. The results indicated that the three methods successfully predicted girth size distributions within the sample stands. The method of moments was the best one with lowest values of Reynolds error index and Kolmogorov-Smirnov statistic however the sylvicultural regimes. The Weibull parameter distribution model developed for each of the two sylvicultural regimes was quite reliable.展开更多
基金sponsored by the Belgiun“Commission Universitaire pour le Developpement(CUD)”-through le Projet In teruniversitaire Cible:Contribution au developpement d’une filiere du teck au depart des forets privees du Sud-Benin(Departement de l’Atlantique)”.
文摘Management of marketable products of private plantations will not be sustainable without class girth being identifiable readily. Modeling marketable products is a key to obtain good fitness between observed and theoretical girth distribution. We determine the best parameter recovery method with the Weibull function for two sylvicultural regimes (coppice and high forest). Data on stand variables were collected from 1101 sample plots. The three Weibull function parameters were estimated with three parameters recovery methods: the maximum likelihood method, the method of moments and the method of percentiles. Stepwise regression and the simultaneously re-estimated parameter using the Seemingly Unrelated Regression Estimation were applied to model each parameter. The results indicated that the three methods successfully predicted girth size distributions within the sample stands. The method of moments was the best one with lowest values of Reynolds error index and Kolmogorov-Smirnov statistic however the sylvicultural regimes. The Weibull parameter distribution model developed for each of the two sylvicultural regimes was quite reliable.
