# SSmicmen

##### Self-Starting Nls Michaelis-Menten Model

This `selfStart`

model evaluates the Michaelis-Menten model and
its gradient. It has an `initial`

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

and `K`

- Keywords
- models

##### Usage

`SSmicmen(input, Vm, K)`

##### Arguments

- input
- a numeric vector of values at which to evaluate the model.
- Vm
- a numeric parameter representing the maximum value of the response.
- K
- a numeric parameter representing the
`input`

value at which half the maximum response is attained. In the field of enzyme kinetics this is called the Michaelis parameter.

##### Value

a numeric vector of the same length as `input`

. It is the value of
the expression `Vm*input/(K+input)`

. If both
the arguments `Vm`

and `K`

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

.

##### See Also

##### Examples

`library(stats)`

```
PurTrt <- Puromycin[ Puromycin$state == "treated", ]
SSmicmen(PurTrt$conc, 200, 0.05) # response only
Vm <- 200; K <- 0.05
SSmicmen(PurTrt$conc, Vm, K) # response and gradient
print(getInitial(rate ~ SSmicmen(conc, Vm, K), data = PurTrt), digits = 3)
## Initial values are in fact the converged values
fm1 <- nls(rate ~ SSmicmen(conc, Vm, K), data = PurTrt)
summary(fm1)
## Alternative call using the subset argument
fm2 <- nls(rate ~ SSmicmen(conc, Vm, K), data = Puromycin,
subset = state == "treated")
summary(fm2)
```

*Documentation reproduced from package stats, version 3.3.3, License: Part of R 3.3.3*

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