Description Usage Arguments Details Value Author(s) References See Also
Methods used for modeling height-diameter relationship
1 2 3 4 5 | loglogFunction(data, method)
michaelisFunction(data, weight = NULL)
weibullFunction(data, weight = NULL)
|
data |
Dataset with the informations of height (H) and diameter (D) |
method |
In the case of the loglogFunction, the model is to be chosen between log1, log2 or log3. |
weight |
(optional) Vector indicating observation weights in the model. |
These functions model the relationship between tree height (H) and diameter (D). loglogFunction Compute three types of log model (log, log2 and log3) to predict H from D. The model can be:
log 1: log(H) = a+ b*log(D) (equivalent to a power model)
log 2: log(H) = a+ b*log(D) + c*log(D)^2
log 3: log(H) = a+ b*log(D) + c*log(D)^2 + d*log(D)^3
michaelisFunction Construct a Michaelis Menten model of the form:
H = (A * D) / (B + D)
(A and B are the model parameters to be estimated)
weibullFunction Construct a three parameter Weibull model of the form:
H = a*(1-exp(-(D/b)^c))
(a, b, c are the model parameters to be estimated)
All the functions give an output similar to the one given by stats::lm()
, obtained for
michaelisFunction
and weibullFunction
from minpack.lm::nlsLM).
Maxime REJOU-MECHAIN, Ariane TANGUY
Michaelis, L., & Menten, M. L. (1913). Die kinetik der invertinwirkung. Biochem. z, 49(333-369), 352. Weibull, W. (1951). Wide applicability. Journal of applied mechanics, 103. Baskerville, G. L. (1972). Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research, 2(1), 49-53.
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