Methods used for modeling height-diameter relationship
loglogFunction(data, method)michaelisFunction(data, weight = NULL)
weibullFunction(data, weight = NULL)
All the functions give an output similar to the one given by stats::lm(), obtained for
michaelisFunction and weibullFunction from minpack.lm::nlsLM).
Result of a model (lm object)
Result of a model (nlsM object)
Result of a model (nlsM object)
Dataset with the informations of height (H) and diameter (D)
In the case of the loglogFunction, the model is to be chosen between log1, log2 or log3.
(optional) Vector indicating observation weights in the model.
Maxime REJOU-MECHAIN, Ariane TANGUY
These functions model the relationship between tree height (H) and diameter (D). loglogFunction Compute two types of log model (log and log2) to predict H from D. The model can be:
log 1: \(log(H) = a+ b*log(D)\) (equivalent to a power model)
log 2: \(log(H) = a+ b*log(D) + c*log(D)^2\)
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)
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.
modelHD()