# SSmicmen

0th

Percentile

##### 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.

nls, selfStart
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)