Skip to contents

Methods used for modeling height-diameter relationship

Usage

loglogFunction(data, method)

michaelisFunction(data, weight = NULL)

weibullFunction(data, weight = NULL)

Arguments

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.

Value

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)

Details

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)

References

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.

See also

Author

Maxime REJOU-MECHAIN, Ariane TANGUY