Models for tree taper form: the gompertz and vasicek diffusion processes framework
Date |
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2020 |
In this work, we employ stochastic differential equations (SDEs) to model tree stemtaper. SDE stem taper models have some theoretical advantages over the commonly employedregression-based stem taper modeling techniques, as SDE models have both simple analytic formsand a high level of accuracy. We perform fixed- and mixed-effect parameters estimation for the stemtaper models by developing an approximated maximum likelihood procedure and using a data set oflongitudinal measurements from 319 mountain pine trees. The symmetric Vasicek- and asymmetricGompertz-type diffusion processes used adequately describe stem taper evolution. The proposedSDE stem taper models are compared to four regression stem taper equations and four volumeequations. Overall, the best goodness-of-fit statistics are produced by the mixed-effect parametersSDEs stem taper models. All results are obtained in the Maple computer algebra system.
Article no. 80
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
Symmetry-Basel | 2.713 | 6.44 | 6.44 | 6.44 | 1 | 0.421 | 2020 | Q2 |
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
Symmetry-Basel | 2.713 | 6.44 | 6.44 | 6.44 | 1 | 0.421 | 2020 | Q2 |
Journal | Cite Score | SNIP | SJR | Year | Quartile |
---|---|---|---|---|---|
Symmetry | 3.4 | 1.097 | 0.385 | 2020 | Q1 |