# SSweibull

##### Self-Starting Nls Weibull Growth Curve Model

This `selfStart`

model evaluates the Weibull model for growth
curve data and its gradient. It has an `initial`

attribute that
will evaluate initial estimates of the parameters `Asym`

, `Drop`

,
`lrc`

, and `pwr`

for a given set of data.

- Keywords
- models

##### Usage

`SSweibull(x, Asym, Drop, lrc, pwr)`

##### Arguments

- x
- a numeric vector of values at which to evaluate the model.
- Asym
- a numeric parameter representing the horizontal asymptote on
the right side (very small values of
`x`

). - Drop
- a numeric parameter representing the change from
`Asym`

to the`y`

intercept. - lrc
- a numeric parameter representing the natural logarithm of the rate constant.
- pwr
- a numeric parameter representing the power to which
`x`

is raised.

##### Details

This model is a generalization of the `SSasymp`

model in
that it reduces to `SSasymp`

when `pwr`

is unity.

##### Value

- a numeric vector of the same length as
`x`

. It is the value of the expression`Asym-Drop*exp(-exp(lrc)*x^pwr)`

. If all of the arguments`Asym`

,`Drop`

,`lrc`

, and`pwr`

are names of objects, the gradient matrix with respect to these names is attached as an attribute named`gradient`

.

##### References

Ratkowsky, David A. (1983), *Nonlinear Regression Modeling*,
Dekker. (section 4.4.5)

##### See Also

##### Examples

`library(stats)`

```
Chick.6 <- subset(ChickWeight, (Chick == 6) & (Time > 0))
SSweibull(Chick.6$Time, 160, 115, -5.5, 2.5) # response only
Asym <- 160; Drop <- 115; lrc <- -5.5; pwr <- 2.5
SSweibull(Chick.6$Time, Asym, Drop, lrc, pwr) # response and gradient
getInitial(weight ~ SSweibull(Time, Asym, Drop, lrc, pwr), data = Chick.6)
## Initial values are in fact the converged values
fm1 <- nls(weight ~ SSweibull(Time, Asym, Drop, lrc, pwr), data = Chick.6)
summary(fm1)
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*

### Community examples

Looks like there are no examples yet.