update.emaxsimobj {clinDR} | R Documentation |
Update estimation in a data set generated by emaxsim
Description
Allows re-estimation for a data set generated by emaxsim using a different starting value. Typically used to test different starting values when nls has failed to converge.
Usage
## S3 method for class 'emaxsimobj'
update(object, new.parm, modType=object$modType,...)
Arguments
object |
Extracted simulation object |
new.parm |
New starting value for Emax estimation. Must have order (ed50,emax,e0) |
modType |
When modType=4, the fitting begins with the 4 parameter model. If estimation fails or modType=3, the 3-parameter estimation is applied. If it fails, a best-fitting model linear in its parameters is selected. |
... |
No other parameters currently used. |
Value
A list is returned with class(emaxsimobj). It has the same format as those extracted by object[ ]
Author(s)
Neal Thomas
See Also
Examples
## Not run:
## emaxsim changes the random number seed
nsim<-50
idmax<-5
doselev<-c(0,5,25,50,100)
n<-c(78,81,81,81,77)
### population parameters for simulation
e0<-2.465375
ed50<-67.481113
dtarget<-100
diftarget<-9.032497
emax<-solveEmax(diftarget,dtarget,log(ed50),1,e0)
sdy<-7.967897
pop<-c(log(ed50),emax,e0)
meanlev<-emaxfun(doselev,pop)
###FixedMean is specialized constructor function for emaxsim
gen<-FixedMean(n,doselev,meanlev,sdy)
D1 <- emaxsim(nsim,gen)
e49<-D1[49]
#### re-try estimation starting at the population value
e49u<- update(e49,pop)
## End(Not run)
[Package clinDR version 2.4.1 Index]