SSlogis {stats} | R Documentation |

## Logistic Model

### Description

This `selfStart`

model evaluates the logistic
function and its gradient. It has an `initial`

attribute that
creates initial estimates of the parameters `Asym`

,
`xmid`

, and `scal`

.

### Usage

SSlogis(input, Asym, xmid, scal)

### Arguments

`input` |
a numeric vector of values at which to evaluate the model. |

`Asym` |
a numeric parameter representing the asymptote. |

`xmid` |
a numeric parameter representing the `x` value at the
inflection point of the curve. The value of `SSlogis` will be
`Asym/2` at `xmid` . |

`scal` |
a numeric scale parameter on the `input` axis. |

### Value

a numeric vector of the same length as `input`

. It is the value of
the expression `Asym/(1+exp((xmid-input)/scal))`

. If all of
the arguments `Asym`

, `xmid`

, and `scal`

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

Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ]
SSlogis( Chick.1$Time, 368, 14, 6 ) # response only
Asym <- 368; xmid <- 14; scal <- 6
SSlogis( Chick.1$Time, Asym, xmid, scal ) # response and gradient
getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
## Initial values are in fact the converged values
fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
summary(fm1)

[Package

*stats* version 2.5.0

Index]