| dc.creator | Madi, João Paulo Sardo | |
| dc.creator | Vendruscolo, Diogo Guido Streck | |
| dc.creator | Silva, Carlos Alberto | |
| dc.creator | Carvalho, Mariana Peres de Lima Chaves e | |
| dc.creator | Carvalho, Samuel de Pádua Chaves e | |
| dc.date | 2017-06-30 | |
| dc.date.accessioned | 2023-08-31T21:51:50Z | |
| dc.date.available | 2023-08-31T21:51:50Z | |
| dc.identifier | https://periodicoscientificos.ufmt.br/ojs/index.php/afor/article/view/4726 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8561784 | |
| dc.description | The aim of this study was to evaluate the performance of probabilistic distribution models for predicting the number of trees in a teak plantation located in the Nossa Senhora do Livramento city, state of Mato Groso, central region in Brazil. In the field, the diameters at breast height (DBH) of 203 trees of seminal origin, at 16 years of age, were measured in 2015. A descriptive analysis of the DBH was performed. Five models were used to fit a diametric distribution of the teak trees at the stand level: Normal, Normal Log, Gamma and Weibull with two parameters (2P) and three parameters (3P). For the purpose of comparison and selection of the best model, the Akaike Information Criterion (AIC) was used. After fitting the models, a simulated dataset was used to compute the accuracy of the number of trees estimated at stand level in each model. Among the fitted models, Weibull 3P was the one that presented the best fit, followed by the Log Normal, Gamma, Normal and Weibull 2P according to the AIC values. For the simulated dataset, the best result was Weibull 2P. When evaluated the accuracy of the model we found a maximum deviance to the Normal Distribution (27.78%). | en-US |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Mato Grosso | en-US |
| dc.relation | https://periodicoscientificos.ufmt.br/ojs/index.php/afor/article/view/4726/pdf | |
| dc.rights | Copyright (c) 2020 Advances in Forestry Science | pt-BR |
| dc.source | Advances in Forestry Science; v. 4 n. 2 (2017): Advances in Forestry Science; 119-123 | pt-BR |
| dc.source | Advances in Forestry Science; Vol. 4 No. 2 (2017): Advances in Forestry Science; 119-123 | en-US |
| dc.source | Advances in Forestry Science; Vol. 4 Núm. 2 (2017): Advances in Forestry Science; 119-123 | es-ES |
| dc.source | 2357-8181 | |
| dc.source | 2359-6570 | |
| dc.source | 10.34062/afs.v4i2 | |
| dc.subject | Probability model | en-US |
| dc.subject | Parametric Statistics | en-US |
| dc.subject | Teak | en-US |
| dc.subject | AIC | en-US |
| dc.title | Univariate models to represent the diametric distribution of thinned stand of Tectona grandis Linn.F | en-US |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
