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Classical logistic growth model written as analytical solution of the differential equation.
grow_logistic(time, parms)
vector of dependent variable (y).
y
vector of time steps (independent variable)
named parameter vector of the logistic growth model with:
y0 initial value of population measure
y0
mumax intrinsic growth rate (1/time)
mumax
K carrying capacity (max. total concentration of cells)
K
The equation used is: $$y = (K * y0) / (y0 + (K - y0) * exp(-mumax * time))$$
Other growth models: grow_baranyi(), grow_exponential(), grow_gompertz2(), grow_gompertz(), grow_huang(), grow_richards(), growthmodel, ode_genlogistic(), ode_twostep()
grow_baranyi()
grow_exponential()
grow_gompertz2()
grow_gompertz()
grow_huang()
grow_richards()
growthmodel
ode_genlogistic()
ode_twostep()
time <- seq(0, 30, length=200) y <- grow_logistic(time, c(y0=1, mumax=0.5, K=10))[,"y"] plot(time, y, type="l")
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