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
SSmicmen(input, Vm, K)
input
value at
which half the maximum response is attained. In the field of enzyme
kinetics this is called the Michaelis parameter.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
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