stats (version 3.3)

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.

encoding

UTF-8

See Also

nls, selfStart

Examples

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)