R: First-order Compartment Model

SSfol {nls} | R Documentation

## 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`.

### Author(s)

Jose Pinheiro and Douglas Bates

### See Also

`nls`, `selfStart`

### Examples

    data( Theoph )
    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)

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