Update estimation in a data set generated by emaxsim
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.
## S3 method for class 'emaxsimobj' update(object, new.parm, modType=object$modType,...)
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. |
A list is returned with class(emaxsimobj). It has the same format as those extracted by object[ ]
Neal Thomas
## 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)
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