stats (version 3.3.3)

SSmicmen: Self-Starting Nls 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.

See Also

nls, selfStart

Examples

Run this code
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)

Run the code above in your browser using DataLab