SSbiexp {stats} R Documentation

## Biexponential model

### Description

This `selfStart` model evaluates the biexponential model function and its gradient. It has an `initial` attribute that creates initial estimates of the parameters `A1`, `lrc1`, `A2`, and `lrc2`.

### Usage

```SSbiexp(input, A1, lrc1, A2, lrc2)
```

### Arguments

 `input` a numeric vector of values at which to evaluate the model. `A1` a numeric parameter representing the multiplier of the first exponential. `lrc1` a numeric parameter representing the natural logarithm of the rate constant of the first exponential. `A2` a numeric parameter representing the multiplier of the second exponential. `lrc2` a numeric parameter representing the natural logarithm of the rate constant of the second exponential.

### Value

a numeric vector of the same length as `input`. It is the value of the expression `A1*exp(-exp(lrc1)*input)+A2*exp(-exp(lrc2)*input)`. If all of the arguments `A1`, `lrc1`, `A2`, and `lrc2` 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

`nls`, `selfStart`

### Examples

```Indo.1 <- Indometh[Indometh\$Subject == 1, ]
SSbiexp( Indo.1\$time, 3, 1, 0.6, -1.3 )  # response only
A1 <- 3; lrc1 <- 1; A2 <- 0.6; lrc2 <- -1.3
SSbiexp( Indo.1\$time, A1, lrc1, A2, lrc2 ) # response and gradient
getInitial(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)
## Initial values are in fact the converged values
fm1 <- nls(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = Indo.1)
summary(fm1)

```

[Package stats version 2.1.0 Index]