stats (version 3.4.3)

SSfol: Self-Starting Nls First-order Compartment Model

Description

This selfStart model evaluates the first-order compartment function and its gradient. It has an initial attribute that creates initial estimates of the parameters lKe, lKa, and lCl.

Usage

SSfol(Dose, input, lKe, lKa, lCl)

Arguments

Dose

a numeric value representing the initial dose.

input

a numeric vector at which to evaluate the model.

lKe

a numeric parameter representing the natural logarithm of the elimination rate constant.

lKa

a numeric parameter representing the natural logarithm of the absorption rate constant.

lCl

a numeric parameter representing the natural logarithm of the clearance.

Value

a numeric vector of the same length as input, which is the value of the expression

Dose * exp(lKe+lKa-lCl) * (exp(-exp(lKe)*input) - exp(-exp(lKa)*input))
    / (exp(lKa) - exp(lKe))

If all of the arguments lKe, lKa, and lCl are names of objects, the gradient matrix with respect to these names is attached as an attribute named gradient.

See Also

nls, selfStart

Examples

# NOT RUN {
Theoph.1 <- Theoph[ Theoph$Subject == 1, ]
SSfol(Theoph.1$Dose, Theoph.1$Time, -2.5, 0.5, -3) # response only
lKe <- -2.5; lKa <- 0.5; lCl <- -3
SSfol(Theoph.1$Dose, Theoph.1$Time, lKe, lKa, lCl) # response and gradient
getInitial(conc ~ SSfol(Dose, Time, lKe, lKa, lCl), data = Theoph.1)
## Initial values are in fact the converged values
fm1 <- nls(conc ~ SSfol(Dose, Time, lKe, lKa, lCl), data = Theoph.1)
summary(fm1)
# }