SSmicmen {stats} | R Documentation |

## Michaelis-Menten Model

### Description

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`

### 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`

.

### Author(s)

Jose Pinheiro and Douglas Bates

### See Also

`nls`

, `selfStart`

### Examples

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
getInitial(rate ~ SSmicmen(conc, Vm, K), data = PurTrt)
## 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)

[Package

*stats* version 2.2.1

Index]