| SSfol {stats} | R Documentation |
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.
SSfol(Dose, input, lKe, lKa, lCl)
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. |
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.
Jose Pinheiro and Douglas Bates
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)