gompGrowth {drc} | R Documentation |
Gompertz growth model, with biologically meaningful parameters. Different parameterisations have been included for specific cases and needs.
gompGrowth.1(fixed = c(NA, NA, NA), names = c("c", "m", "plateau")) gompGrowth.2(fixed = c(NA, NA, NA), names = c("c", "d", "plateau")) gompGrowth.3(fixed = c(NA, NA, NA), names = c("b", "c", "plateau"))
fixed |
numeric vector. Specifies which parameters are fixed and at what value they are fixed. NAs for parameter that are not fixed. |
names |
vector of character strings giving the names of the parameters (should not contain ":"). The default parameter names are: init, m, plateau. |
The Gompertz growth model is a Gompertz curve, that has been reparameterised to include some biologically meaningful parameters. The mean function for gompGrowth.1() is:
f(x) = f(x) = plateau * exp ( - (m/c) * exp ( - c * x ) )
The parameter plateau is the final plant weight, reached for x going to infinity the parameter c is relative growth rate at inflection point and the parameter m is the initial relative growth rate (when x=0). Thus the curve is monotonously increasing in x. The mean function for gompGrowth.2() is:
f(x) = plateau * exp ( - exp ( c * ( d - x ) ))
where the parameter c is the relative growth rate at inflection point and the parameter d is the abscissa of the inflection point. The mean function for gompGrowth.3() is the classical Gompertz function:
f(x) = plateau * exp ( - b * exp ( - c * x ) )
where b is proportional to the initial relative growth rate (m = b * c).
A list of class drcMean
, containing the mean function, the self starter function,
the parameter names.
Growth functions are generally fitted on log-transformed weight data, which equals to setting bc parameter to 0
Andrea Onofri
Roderick Hunt, 1982. Plant Growth Curves. Edward Arnold Publisher, Great Britain, 248 pp
## Fitting a Gompertz growth curve beet.model <- drm(weightInf ~ DAE, data = beetGrowth, fct=gompGrowth.1()) plot(beet.model, log = "") summary(beet.model)